Product

Product announcements, new feature launches, and roadmap updates — everything you need to stay current on evolving GreyNoise solutions.

Introducing Tactics: See What Adversaries Do After They’re Inside

GreyNoise has spent years observing the earliest stages of an attack. Our Global Observation Grid sees adversaries as they scan the internet, probe exposed systems, and attempt to exploit vulnerabilities at the edge. That visibility has traditionally focused on the left side of the MITRE ATT&CK framework, from Reconnaissance through Initial Access and it’s where we built our primary-source intelligence brand.

But we’ve known that is only half the equation.

Moving Further Right on MITRE ATT&CK

Earlier this year, we launched our C2 Detection Module, expanding our visibility beyond inbound scanning to the attacker-controlled infrastructure used after exploitation. GreyNoise reads the callback destinations embedded in exploit payloads to identify where a compromised device would call home, from malware-hosting servers to suspected C2 infrastructure.

This marked our first move right of Initial Access on MITRE ATT&CK, extending visibility beyond the exploit itself to the infrastructure supporting what happens next. Defenders can match outbound traffic from their edge devices against GreyNoise callback intelligence to identify connections to confirmed malware-serving infrastructure or suspected C2 servers.

See Host Telemetry from GreyNoise Deception Sensors on Your Network 

When we launched Project Swarm, we opened our deception platform to the global security community. Participants could deploy GreyNoise Deception Sensors across their own infrastructure that looked like the firewalls, routers, VPN gateways, and other internet-facing systems that adversaries target.

Project Swarm users gained full visibility into the sessions reaching their sensors, including raw payloads, HTTP headers, TLS metadata, and other behavioral artifacts. 

But a common ask from them was deeper visibility into what happened after an exploit succeeded. What shell commands did the adversary run? What files did they touch? What did they try to do next?

Introducing GreyNoise Tactics

Today, we are launching Tactics, giving anyone deploying a GreyNoise Deception Sensor deeper visibility into what attackers do after initial compromise. 

Tactics automatically maps qualifying attacker sessions captured by sensors in your workspace to the MITRE ATT&CK framework. Each detection represents one session and shows the tactics and techniques observed, along with the activity behind the mapping.

You can find Tactics under Observe → Tactics in the GreyNoise Visualizer. Open a detection to:

  • Follow the attacker’s complete command sequence
  • See the commands, scripts, and binaries the adversary executed
  • Inspect files created or modified, including their SHA256 hashes
  • Review outbound connections to internet destinations
  • Identify attempts to move laterally within your address space

Tactics begin populating when your workspace has a sensor running a vulnerable profile. Once an attacker compromises that profile and performs activity mapped to a MITRE ATT&CK technique, the session will appear as a detection.

Routine and unclassified sessions are filtered out, so the view focuses on meaningful adversary behavior rather than every connection your sensor receives.

See What Happens After the Shell

Because GreyNoise captures the attacker’s interaction with the host, Tactics can identify behavior across the post-compromise stages of MITRE ATT&CK.

That includes:

  • Execution: Commands, scripts, and binaries run after gaining access
  • Persistence: Scheduled jobs, new accounts, and other attempts to maintain access
  • Privilege Escalation: Attempts to gain greater control of the host
  • Defense Evasion: Actions intended to hide activity or interfere with protections
  • Credential Access: Searches for cloud credentials, private keys, service account tokens, and other secrets
  • Discovery: Commands used to inspect the operating system, processes, files, and surrounding environment
  • Lateral Movement: Attempts to reach other systems from the initial foothold, a view that keeps expanding as our deception network grows 
  • Collection: Files and data gathered from a system they think they’ve compromised 
  • Command and Control: Connections used to retrieve payloads or maintain access
  • Exfiltration: Attempts to move credentials, files, or other data off the sensor
  • Impact: Activity intended to disrupt the host, consume resources, or interfere with processes

With Tactics, GreyNoise now shows what adversaries do with access, not just how they find and exploit exposed systems.

Turn Observed Behavior Into Action

Every command, file, hash, path, and network connection captured by a sensor gives defenders a lead they can investigate inside their own environment.

  • SOC analysts and detection engineers can build and tune detections around the commands and techniques adversaries are using now.
  • Threat hunters can search production environments for observed hashes, file paths, binaries, and command patterns.
  • Threat intelligence teams can track which tactics and techniques are appearing across infrastructure relevant to their organization.

Because this intelligence comes directly from observed session activity, defenders can work from what the adversary actually did after gaining access. Mapping that activity to MITRE ATT&CK makes it easier to understand and use across existing security workflows.

What We Found After the Shell

Before launching Tactics, we analyzed weeks of post-compromise activity across our own Deception Sensor network in the Global Observation Grid.

Much of what we observed was commodity cryptomining, with adversaries treating each new foothold as more infrastructure to consume. A smaller set of sessions showed more serious behavior, going after cloud credentials, attempting container escapes, or creating backdoor accounts.

We break down these findings in After the Shell, a new GreyNoise research report published today. It examines what adversaries did after gaining access, which behaviors appeared most often, and what those observations mean for defenders.

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Join the Swarm

Tactics is available for all users who have deployed a GreyNoise sensor. If you already have a sensor deployed, open Tactics under Observe in the GreyNoise Visualizer to see what it has captured.

If you’re new to Project Swarm, deploy a Greynoise Deception Sensor to start observing what attackers do after compromise.

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GreyNoise Tags Its Way to 1337 Elite Status

Yesterday, GreyNoise reached a fun and significant milestone after publishing our 1,337th tag. 1337 is a cherished number in hacker culture, as it is a numerical shorthand for "leet", which itself stands for "elite". This term has deep roots, going all the way back to the 80's when one had to make modems scream to access bulletin board systems (now, we humans are the ones screaming whenever we go online to see what fresh hades awaits us each day).

What makes this milestone even more significant is how it was achieved.

The chart, below, shows the cumulative sum of tag counts by year. While there was a modest improvement in intra-year tag creation from 2022 to 2023, we're just into the first few weeks of Q2 in 2024 and are almost at the total tag count for 2023.

We will almost certainly blow past 2023's tag count well-before the end of Q2, and this has all been made possible by our focused and practical use of AI. This system helps our incredible detection engineers quickly triage the millions of events our sensor fleet absorbs every day. With it, they discover and tag novel payloads to help inform and protect our customers, community, and the internet as a whole. The application that fuels this work is called Sift, and we've waxed poetic about it quite a bit over the past few months.

This boost to the tag inventory has also meant an increase in CVE coverage.

(Since it most likely drew your attention, the jumps in 2022 were due numerous factors, including the increase in Russian hostilities towards Ukraine.)

60% of 2024 tags are based on CVEs, and — along with plenty of "modern" vulnerabilities — Sift has helped us catch exploitation attempts of some very old CVEs, too:

I'm incredibly proud of our team of data scientists, security researchers, and detection engineers. Their leet expertise powers the detections that folks rely on every day, and we hope you'll join in our celebration of achieving this epic milestone!

To learn more about GreyNoise tags and how they differ from "traditional" detections, check out our Tags Webinar Series.

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Leveraging AI Advances to Improve Intelligence for Discovery, Identification, and Interpretation

AI is so hot right now, and the cybersecurity space is no exception. Technology leaders are unveiling exciting new capabilities, vendors are making extravagant claims, and practitioners are working hard to understand how to separate the wheat from the chaff, leveraging AI where it can make the most difference to their operations’ and their organization’s risk.

Here at GreyNoise, we’ve been investigating where AI capabilities can have the biggest impact, and then working to deploy them internally, externally, and in partnership with other security vendors. In this blog we’ll discuss several GreyNoise AI projects and how they’re helping defenders identify and understand threats and secure their environment.

Sift: AI for Anomaly Discovery

Traditional automation is rule-based and rigid. “IF a packet matches this malware signature, THEN block it AND generate an alert”, etc. AI-based approaches are different. AI makes it possible to automate pattern recognition—and its inverse, anomaly discovery. With AI, defenders can rapidly process high volumes of data, and automatically identify the most suspicious observations for high-priority analysis and triage.

Sift is GreyNoise’s tool for solving this problem. It leverages multiple advanced AI techniques, including: 

  • custom-built LLMs (Large Language Models) 
  • nearest neighbor search and vector databases 
  • unsupervised clustering

Sift runs daily, helping our research team process the data generated by our global sensor fleet to identify novel behavior, traffic, and attacks.

For more on Sift and how it works, check out our technical launch blog here. 

Sift: AI for Targeted Attack Identification

But Sift doesn’t stop there. The same techniques can be applied to the data generated by targeted subsets of our sensors, helping specific organizations generate intelligence insights and reports tailored to observations from their own networks. This AI application will bring the industry-leading research capabilities of GreyNoise into any organization’s internal security processes, reducing triage overhead, accelerating attack identification, and making life easier for defenders—and harder for attackers.

For more on how to bring the insights of Sift into your own organization, talk to our team.

Copilot: AI for Interpretation

The capabilities of AI aren’t limited to stochastic data analysis. Recent advances in transformer architectures and LLMs have cracked the natural language barrier, making it possible to generate well-formulated utterances at scale. This has opened up a new frontier of AI assistants. Microsoft Copilot for Security is leading the charge to bring these capabilities into the cybersecurity space, and GreyNoise is working together with Microsoft on this initiative. We’re a partner in the Microsoft Copilot for Security Partner Private Preview, and our plug-in means that both free and enterprise users can access GreyNoise insights from within their Copilot interface with natural language prompts.

For more on how GreyNoise and Microsoft Copilot for Security work together, check out our dedicated integration page.  

The Future of AI

The future of AI is hard to predict, and the evolution of the field has famously surprised both boosters and skeptics. Organizations looking to leverage these rapidly transforming capabilities will need to roll with the punches—and continue to partner with security vendors who can do the same. Here at GreyNoise we’re committed to doing just that. We’re excited to share how AI is already empowering our security—and we can’t wait to see what’s next.

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Battling Ransomware One Tag At A Time

In October 2023 — as part of the Ransomware Vulnerability Warning Pilot (RVWP) — CISA began tagging entries in their Known Exploited Vulnerabilities (KEV) catalog. This field designates whether exploits for a given vulnerability are known to be used in ransomware attacks. Ransomware has disrupted critical services, businesses, and communities worldwide, and many organizations are working diligently to get ahead of these attacks to prevent losses, disruptions, and exposures.

We’ve talked about this topic before, but today we dig a bit deeper into the topic with some specific guidance as to how your organization can fight the good fight against these foes by leveraging the power of GreyNoise tags.

GreyNoise Tags vs. Ransomware

As scores of organizations who use them know, GreyNoise tags are a signature-based detection method that categorizes internet noise into actionable intelligence. As of this writing, we’ve observed recent activity in 63 tags that CISA has identified as being used in association with ransomware attacks. The figure at the beginning of this post shows the frequency and volume of this opportunistic activity. One striking feature of this activity is the diversity of targeted platforms.

In the case of internet-facing attack campaigns, one might assume that vulnerabilities targeted by ransomware actors would lean towards remote access technologies. The chart and our data that backs it up shows that almost no technology category is safe from these types of attacks. Collaboration tools, such as Atlassian Confluence or JetBrains TeamCity; email platforms, such as Microsoft Exchange; software that powers application middleware services, such as Jboss and WebLogic; or, even devices that are intended to help elevate safety and resilience, such as SonicWall, Ivanti, Citrix, and Fortinet are all regularly targeted.

If you use any of these technologies, knowing when new activity is seen can be helpful in shoring up defenses and readying response activities. By leveraging GreyNoise platform features, such as our Alerts and block lists, security teams can, respectively, determine if more focus should be placed on monitoring key systems and preventing opportunistic harm. With the noise weeded out, response teams can focus their attention on similar activity that is likely to be more targeted, which may also mean by more capable adversaries. And, because we play incredibly well with a host of other security tools, teams can also save time, and use our intelligence within familiar environments.

The Long, Sporadic Tail Of Ransomware Tag Activity

Another striking feature of our ransomware tag activity chart is the diversity of activity. Cloud deployments top the list, with attackers looking to take advantage of misconfigurations that may arise in these highly dynamic environments. Broad and commonly deployed technologies are also regular targets, since these systems can also become victims of errant misconfigurations, especially when restored from unpatched backups.

However, as we move down the list, the frequency becomes far more sporadic, and many involve only single hosts vs. botnet armies. This can be due to attacker familiarity, or individual actors keying off results from well-timed Censys or Shodan searches that show newly exposed vulnerable configurations. If your organization uses any of these components, there truly is no rest from vigilance.

The Ransomware GNQL Listicle

To help defenders get a leg up on these attacks, the list below has links to each individual tag that’s known to be used in ransomware attacks. At each tag page, you can find the block list URL which you can use to immediately weed out the opportunistic noise. Wrap one or more of them inside a GNQL query, such as tags:"F5 BIG-IP iControl RCE Attempt", and you can set up an alert to notify you when new activity is seen, especially in generally dormant tags.

Find Out More

If you're curious as to just how GreyNoise researchers craft our tags we have a three-part webinar series that discusses the makeup of our tags, walks you through how we discover what needs to be tagged, and illustrates how AI is empowering the creation of new tags and detections:

Not a GreyNoise customer — yet? Sign up and take our platform for a free enterprise trial to see all the features and data available.

Elevating Threat Intelligence with GreyNoise and Microsoft Sentinel

GreyNoise has recently released a new integration for Microsoft Sentinel, enhancing the capabilities of threat intelligence for business security. This integration provides security professionals with valuable insights into internet-wide scanning and reconnaissance activities. Tailored to offer a streamlined feed of threat indicators, it enables proactive threat identification and mitigation. Users can now leverage GreyNoise data within their threat-hunting queries and any analytics rules.

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GreyNoise indicators in Microsoft Sentinel

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One of the most exciting aspects of our new integration is the seamless combination of GreyNoise’s data with Sentinel’s threat-hunting capabilities. Analysts now have a unique, robust ability to utilize GreyNoise data when investigating potential malicious patterns and anomalies within their network events. The integration also allows filtering out known opportunistic traffic during threat hunting to identify more targeted and malicious activity better. 

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Modified threat-hunting queries to filter out indicators from GreyNoise

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To further enhance detection capabilities, the new content pack also introduces a set of analytics rules designed to identify and mitigate potential threats. By incorporating these indicators into analytics rules, security teams can take a more proactive approach to identifying known malicious behavior. By taking this approach, detections are elevated, and organizations can stay ahead of malicious actors that are commonly looking for exposed, vulnerable devices and misconfigured applications. 

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In conclusion, integrating GreyNoise with Microsoft Sentinel offers a strategic advantage in navigating the cybersecurity landscape. By combining indicators from GreyNoise with analytics rules, hunting queries, and existing automation workflows, analysts now wield an indispensable toolkit to combat evolving threats proactively.

Explore the latest content pack available on the Azure marketplace to start ingesting GreyNoise indicators into Microsoft’s Sentinel’s threat intelligence platform. You' will need a current GreyNoise trial or Enterprise license to access the GNQL API endpoint for data ingestion.  If you do not have access to either, contact us for more information and to get started.

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Getting A Leg Up On Initial Access Ransomware With CISA KEV and GreyNoise Tags

The Cybersecurity and Infrastructure Security Agency (CISA) has added a field to their Known Exploited Vulnerabilities (KEV) catalog that denotes if a KEV CVE has been used in ransomware attacks. Over two hundred KEV CVEs fall into this category, 75 of which (~35%) have corresponding GreyNoise tags. GreyNoise's planetary fleet of sensors are designed to catch remote Initial Access attacks, and most ransomware exploits in KEV fall outside this category.

The addition of this ransomware designation has proven to be valuable for defenders. It provides a critical data point that may help them gain traction for interrupting normal operations so that teams can focus on patching and applying mitigations to prevent a potentially devastating incident from occurring.

As the chart below shows, GreyNoise meets or beats KEV when it comes to having detections and actionable intelligence available after a CVE has been published. Since many ransomware gangs hide their activities in the same compromised devices that GreyNoise tracks daily, this gives organizations that use GreyNoise IP intelligence block lists a significant advantage over those that do not. You can effectively negate the onslaught of the majority of opportunistic ransomware attacks and campaigns of initial access brokers by using the hourly updated telemetry provided by the GreyNoise platform.

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Extending Your Lead

To stay even further ahead of our combined adversaries, GreyNoise account holders can join in the fight by sifting through the novel daily clusters of malicious events that assault our fleet every minute of each day.

We’ve talked about Sift before, and the GreyNoise Labs and Design teams recently enhanced the user experience, streamlining the user interface and integrating more tools to make it easier to spot potentially new and malicious traffic.

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Know. More. Noise

Not a GreyNoise customer — yet? Sign up and take our platform for a free enterprise trial to see all the features and data available.

GreyNoise Round-Up: Product Updates - June And July 2023

As we roll through the summer, GreyNoise is back from its July two-week shutdown with a bunch of fresh new improvements, including 63 new tags and a bunch of exciting new data insights for our customers to explore in our Labs API.  We’ve also updated our integrations to add support for our Timeline for our Palo Alto customers.

New: Explore C2 Data, HTTP activity, and more

topC2s

Access the top 10% of possible Command and Control (C2) IP addresses, ranked by their pervasiveness, observed by GreyNoise over the previous 24 hours. Use this query to identify second-stage IP addresses that might be involved in malicious activities following the reconnaissance and initial access stages. 

topHTTPRequests

Access the top 1% of HTTP requests, ranked by their pervasiveness, observed by GreyNoise over the last seven days. Gain insights into the background radiation of the internet, exploring the patterns and trends of HTTP requests.   

topPopularIPs

Access the top 1% of IPs searched in GreyNoise, ordered by the number of users observed searching over the last 7 days. Understand commonalities in how users search within GreyNoise, gaining insights into popular IPs and their associated activities. This query uses a minimum number of IP submissions and users to build consensus before an IP can be considered available in this dataset.

noiseRank

Access the top 1% of IPs by their noise score for the last 7 days. This score is determined by comparing the pervasiveness of the number of sensors and countries that observed packets from the IP, the request rate, and the diversity of payloads and ports for which the packets were observed.  This query is intended to help rank the top noise makers compared to the quiet single-hit scanners. 

Enhancement: Create an Alert for a Tag From the Tags Action Panel

We’ve added a “Create Alert” button in the Action panel on the Tag details page to make it easy to create an alert. GreyNoise users can use this to monitor scanning activity directly from the Tags page, informing them of any new IPs scanning for tags they are interested in.

Enhancement: Copy/Search Fields On IP Details

There is now a Copy/Search button in fields on the IP details page. The previous behavior did not allow users to copy the values in the fields.

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You can access the Copy/Search buttons by hovering over fields such as Ports Scanned, Country, OS in the IP Details pages.

Enhancement: Analysis File Size Increased to 4MB

Previously, the Analysis Feature only accepted inputs up to 2MB.  We've increased this to 4MB, so that customers can submit larger files without getting an error. 

New and Updated Integrations

Palo Alto XSOAR (Demisto) Improvements: IP Timeline Support

We updated our Palo Alto XSOAR support to include our  IP Timeline features, allowing users to easily find similar IP addresses, or review GreyNoise’s classification history on an IP.

To learn more about using the XSOAR Demisto enhancements for IP Timeline, you can check out our documentation.

Tags Coverage Enhancements

In June & July, GreyNoise added 63 new tags:

56 malicious activity tags

2 benign actor tags

5 unknown tags

All GreyNoise users can monitor scanning activity we’ve seen for a tag by creating an alert informing them of any new IPs scanning for tags they are interested in.

Notable Security Research and Detection Engineering Blogs:

Don't have a GreyNoise account? Sign-up for free.

How to Leverage GreyNoise in Your SOAR Playbooks

During our latest webinar Proactive Defense Made Easy: Leveraging GreyNoise in Your SOAR Playbooks, we discussed some everyday use cases using GreyNoise with other SOAR platforms. The main goal of using GreyNoise with other SOAR platforms is to quickly identify either opportunistic attacks, get better insight into how infrastructure is being used, as well as enriching alerts using RIOT data to IP's associated with common business services.

Using GreyNoise to identify opportunistic scanning provides context to decisions in a SOAR playbook to either decide to investigate further or more quickly move to block IP's. Adding the checks into an investigation playbook provides data on scan activity and any vulnerabilities observed as being exploited.

A Tines story that uses GreyNoise as the first step to decide additional investigations needed.

RIOT data also provides quick data for an investigation. Many services integrated into an investigation playbook will provide details for when something is malicious but often don't provide details on known or known good services. Everyone wants the confidence to take action with their automation but may not have the insight needed. Additionally, no one wants to be wrong about this decision. RIOT adds this information to a playbook to assist with decision-making.

Phishing email in XSOAR identifying office 365 emails using RIOT data.

GreyNoise can be used in common SOAR use cases to provide better context to phishing playbooks and investigations and have more confidence to block IP's. The power of GreyNoise, alongside other intelligence tools like Recorded Future, VirusTotal, Tines, and Splunk, is nothing short of astonishing(see our full list of integrations). I hope the insights shared during the webinar inspired you to explore these tools further and optimize your cybersecurity investigations. Sign in/up for GreyNoise to explore our data for free.

Watch the full webinar

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Splunk and GreyNoise Integration: Discovering Hidden Insights through Feeds and Dashboards

If you’ve ever seen a GreyNoise presentation by me, it’s more than likely at some point I will pull up my Splunk instance to show what I would consider to be a few clever dashboards and searches. Apart from the impromptu searches that I may write (which may not be great), there’s some powerful and practical ways you can leverage GreyNoise data inside your Splunk environment right now.

Feeds

With the latest version of the GreyNoise app for Splunk (v.2.2.0), you can now keep the last 24 hours of data local to your Splunk instance with feeds. Plus, it’s easier than ever to filter out noise from large datasets. Instead of relying on API lookups, the data can be referenced locally first to remove opportunistic and benign IP’s quickly when hunting through your data.

Filtering web logs by IP’s not observed by GreyNoise: index=main sourcetype=access_combined | lookup greynoise_indicators.csv ip as clientip| search NOT classification=benign

Dashboards

A good dashboard can turn a bad day into a great one.

I always joke that data isn’t real until it’s displayed on a map, but there's some truth to it! Having a quick overview of your data visually makes it easier to piece together an understanding of the scan activity landscape.

Using custom commands you can pull out information on internet traffic to safely and confidently ignore (things we classify as ‘benign’ or IP’s from the RIOT dataset) and particular pieces of information you may want to investigate further. Everything left over will include the IP’s that are not in GreyNoise, which could indicate more targeted attacks, and IP’s we classify as ‘unknown’.

You can find more information about our classifications and how to apply GreyNoise data to your analysis in our documentation: https://docs.greynoise.io/docs/applying-greynoise-data-to-your-analysis

Paired with information from your firewall imported into Splunk, GreyNoise data leveraged in a dashboard can show vulnerabilities that ‘unknown’ IP’s are specifically looking for. Combining this knowledge with your current vulnerability scans can help you quickly identify if someone is interested in vulnerabilities specific to your attack surface.

Using GreyNoise with firewall data to build a dashboard to find potentially targeted activity as well as provide details for how IP addresses are operating.

Known Good

We talk a lot about filtering out opportunistic traffic, and enriching data based on GreyNoise but let’s not sleep on the RIOT dataset. If you’re not familiar with RIOT it’s a collection of ~50 million IP addresses that are associated with common business services.

What does this let you do with your data in Splunk? There’s a lot of ways that people are applying this dataset in their searches and hunting. Ryan Kovar wrote a great blog post about using wiredata with Splunk (https://www.splunk.com/en_us/blog/security/wire-data-huh-what-is-it-good-for-absolutely-everything-say-it-again-now.html) and while legitimate services can be abused (Hello T1567!) they can also make up a significant portion of the traffic being searched. RIOT makes it easy to do a first pass and remove any outbound traffic to those services and makes it easier to find potentially interesting traffic.

Using RIOT to summarize outbound network activity using Squid proxy data: index=main source=squid:access | gnriot ip_field=src | rename greynoise_name as organization | stats count by organization

More on our RIOT dataset here: https://docs.greynoise.io/docs/riot-data

Learn More About GreyNoise + Splunk

If you find this information useful then join me on June 15th for a live webinar where I’ll cover the Splunk integration in detail.

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GreyNoise Round Up: Product Updates - May 2023

May brought more product enhancements to user workflows, data coverage… and of course, more interesting tags! Twenty four to be exact, as we continue to improve our product to help our customers monitor emerging threats and identify benign actors. We improved our sensor coverage to include coverage in the country of Ghana, plus we made some helpful improvements to our bulk analysis, RIOT dataset, and APIs.  

Improvement to Bulk Analysis: Export Unknown IPs

The Bulk Analysis function in the GreyNoise Visualizer has been improved so that users can now export unidentified IPs via CSV and JSON.  

This improvement helps analysts more easily identify the ‘interesting’ IPs in a bulk dataset that they are analyzing (IPs identified by GreyNoise are identified to be known common scanners or common business services; IPs that are UNKNOWN in GreyNoise could represent a targeted threat or something that requires additional investigation). 

To access this feature, go to the GreyNoise Analysis page and analyze a file or dataset containing IP addresses.

Improvements to Destination Metadata: Sensor Hits

Two fields have been added to the metadata returned via Bulk Data, IP Context API, and GNQL API that will help users determine baselines or rates of activity:

  • metadata.sensor_hits is the amount of unique data the sensor has recorded from the queried IP.
  • metadata.sensor_count is the number of our sensors from which the IP address or behavior has been observed.

RIOT: Qualys Scanner IPs added

We are now tracking Qualys scanner IP addresses in our RIOT database of common business services, so that customers can whitelist this activity (should they wish to) or contextualize this activity when seen in their security logs.

RIOT identifies IPs from known benign services and organizations that commonly cause false positives in network security and threat intelligence products. The collection of IPs in RIOT is continually curated and verified to provide accurate results.

New and Updated Integrations

Splunk Improvements: High Volume Enrichment, IP Similarity and IP Timeline Support

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The GreyNoise App for Splunk has been updated to include a new Feed component, which allows users to ingest the GreyNoise indicator feed into Splunk to be used for high-volume log enrichment. Additionally, new dashboard and commands have been added to support the IP Similarity and IP Timeline tools.  Learn More

ThreatQ Improvements: New Actions for ThreatQ Orchestrator

ThreatQ has released new GreyNoise Actions for the Orchestrator platform which allow for IP Similarity, RIOT and Quick lookups against the GreyNoise API. These updates can be downloaded from the ThreatQ Marketplace.  Learn More

Tags Coverage Enhancements

In May, GreyNoise added 24 new tags:

20 malicious activity tags

3 benign actor tags

1 unknown tag

All GreyNoise users can monitor scanning activity we’ve seen for a tag by creating an alert informing them of any new IPs scanning for tags they are interested in.

Notable Security Research and Detection Engineering Blogs:

KEV'd: CVE-2021-45046, CVE-2023-21839, and CVE-2023-1389

On Monday, May 1, 2023, CISA added CVE-2021-45046, CVE-2023-21839, and CVE-2023-1389 to the Known Exploited Vulnerabilities (KEV) list.  For all three CVEs, GreyNoise users had visibility into which IPs were attempting mass exploitation prior to their addition to the KEV list. GreyNoise tags allow organizations to monitor and prioritize the handling of alerts regarding benign and, in this case, malicious IPs.

Trinity Cyber + GreyNoise: Sharing Intelligence to Protect Internet Citizens

At GreyNoise we recognize the value of partnership and intelligence sharing when it comes to protecting internet citizens. Today the GreyNoise Labs team wants to give a shoutout to Trinity Cyber.

Progress’ MOVEit Transfer Critical Vulnerability: CVE-2023-34362

On May 31st, 2023 Progress issued a security notice to users of MOVEit Transfer regarding a vulnerability that allows for escalated privileges and potential unauthorized access to the environment. CVE-2023-34362 was assigned to this vulnerability on June 2, 2023.

Sensor Coverage Enhancements: Ghana

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We’ve added additional sensor coverage for the following countries:

You can view which IPs are seen scanning sensors in certain countries from our IP details page, or use `destination_country:”<country_name>”` in GNQL to find IPs that have hit those regions.  Destination country search is available in all commercial plans for GreyNoise and to our community VIP users.

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GreyNoise Round Up: Product Updates - April 2023

GreyNoise added a number of exciting updates in April, including 20 new tags for users to monitor emerging vulnerabilities and threats, and identify benign actors. We’ve also added integration updates to support our IP Timeline feature.

IP Timeline Enhancements 

GreyNoise IP Timeline Enhancements

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90 Days of IP Timeline Data Now Available

We’ve enhanced our IP timeline feature to store up to 90 days of IP history data (previously, we provided up to 60 days of data) to enable customers to better understand historical IP activity when threat hunting or performing incident response.  IP Timeline is available to paying customers and to our community VIP users: start a trial* today to explore or learn more about this feature.

New and Updated Integrations

Integration Update: Anomali ThreatStream Enrichment

GreyNoise Similarity Intel

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We updated our Anomali ThreatStream Enrichment to include our IP Similarity and IP Timeline features. From the context of an observable, customers can now see all details GreyNoise knows, plus view similar IPs and the timeline of observed activity. Learn More

New Integration: Anomali ThreatStream Malicious IP Feed

Our Malicious IP Feed is now available on the Anomali ThreatStream marketplace. Customers can now easily subscribe to the feed and get a daily update of malicious IPs that GreyNoise observed scanning the internet in the last 24 hours. Learn More

Integration Update: Splunk SOAR

We updated our Splunk SOAR integration to introduce two new commands: "similar noise ips" and "noise ip timeline". These commands pull data from the GreyNoise IP Similarity and IP Timeline features and allow customers to bring that context into Splunk SOAR for an analyst to use during an investigation.  Learn More

Integration Update: Maltego

We updated our Maltego Enterprise transform set to include a new Transform that allows for users to query for Similar IPs.  This leverages the new IP Similarity tool, and allows for Maltego users to bring similar IPs into their graph for additional research and correlation within Maltego.  Learn More

Integration Update: GreyNoise SDK

The GreyNoise SDK has been updated to include both CLI and API based commands to interact with the new IP Timeline and IP Similarity APIs. Learn More

Tags Coverage Enhancements

In the month of April, GreyNoise added 20 new tags:

10 malicious activity tags

6 benign actor tags

4 unknown activity tags

All GreyNoise users can monitor scanning activity we’ve seen for a tag by creating an alert that will inform them of any new IPs scanning for tags they are interested in.

Notable Security Research and Detection Engineering Blogs:

Change in ENV Crawler Tags as Bots Continue to Target Environment Files

On Tuesday, April 25, 2023, GreyNoise is changing how we classify environment file crawlers from unknown intent to malicious intent.  At the time of publication, this change will result in the reclassification of over 11,000 IPs as malicious.  Users who use GreyNoise’s malicious tag to block IPs based on malicious intent will see an increase in blocked IPs.

Active Exploitation Attempts (CVE-2023-1389) Against TP-Link Archer Gigabit Internet Routers

In collaboration with our partner Trinity Cyber, GreyNoise has a new tag for scan traffic related to CVE-2023-1389, a pre-auth command injection weakness in TP-Link Archer routers.

New Vulnerability: PaperCut MF/NG

On Friday, April 21, 2023, CISA added CVE-2023-27350 (a critical unauthenticated remote code execution vulnerability) impacting PaperCut MF and PaperCut NG to the Known Exploited Vulnerabilities (KEV) list.  PaperCut MF and PaperCut NG are both enterprise printer management software. 

A Trio of Tags For Identifying Microsoft Message Queue Scanners And Exploiters Live Now - QueueJumper (CVE-2023-21554)

Check Point Research discovered three vulnerabilities in Microsoft Message Queuing (MSMQ) service, patched in April's Patch Tuesday update. The most severe, QueueJumper (CVE-2023-21554), is a critical vulnerability allowing unauthenticated remote code execution. GreyNoise has a tag, classified as malicious, for the full QueueJumper RCE Attempt.

Sensor Coverage Enhancements

GreyNoise Sensor Coverage Enhancements

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We’ve added additional sensor coverage for the following countries:

Destination country search is available in all commercial plans for GreyNoise and to our community VIP users. Start a trial* today to explore destination data.

Search Enhancements

GreyNoise Search Enhancements

The GNQL cheat sheet is now available in the search bar.  Want to learn more about how to effectively use GNQL? Review the cheat sheet for some helpful examples around syntax and available fields to use in search.

(*To begin your GreyNoise Enterprise Trial, sign-in to your account or sign-up for a free account, then go to your account details page and select "Start Trial".)
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Work Smarter, Not Harder: How to Upgrade Your Threat Intel Program in 2023

Cyber threats are constantly evolving, and organizations need to stay on top of the latest techniques and tools to protect themselves against attacks. One of the most critical aspects of this is having an effective threat intel program in place. But how do you upgrade your program to keep up with the ever-changing threat landscape? Our answer: start looking for patterns in attack telemetry.

David Bianco’s ‘Pyramid of Pain’ illustrates the relationship between the types of indicators you might use to detect an adversary's activities and how much pain it will cause them when you are able to deny those indicators to them. Organizations can better identify and defend against threats by moving from simple indicators like domains, hashes, and IPs to focusing on more difficult to change indicators such as TTPs. While gaining this additional insight can take more time, defenders can do more to detect and prevent future attacks.

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The Pyramid of Pain | Source: David Bianco

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GreyNoise data is awesome, but in order to move from IPs -> TTPs, we have built new features to help you upgrade your Threat Intel program (thanks to the Pyramid of Pain)!

IP Similarity

It is now easier than ever to fingerprint attacker infrastructure. This new feature clusters activity based on similar behavior, like similar HASSH and JA3 fingerprints, RDNs, user agents, and ports scanned. Based on the results from IP Similarity, you can hunt within your own network to proactively find other related malicious activity.

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GreyNoise IP Similarity Dashboard comparing HASSH Fingerprints of two IPs 71.6.199[.]23 and 89.248.172[.]16


IP Timeline

The IP Timeline displays activity as seen by GreyNoise sensors of a particular IP Address over the past thirty days. By checking our timeline graph, you can see when an IP interacts with our sensors. This chron data helps CTI teams identify if an attacker is using an automated process or if the scan/attack process is manual.

GreyNoise IP Timeline view for 41.65.223[.]220

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Understanding how adversaries operate and adopting a defined strategy to detect and remediate can lead to a more effective threat intelligence program. GreyNoise can be used to easily enrich threat feeds to gain deeper insight into how attacker infrastructure is being used and quickly understand what services, devices, and vulnerabilities they want to leverage as part of their campaign.

If you are interested in learning more about any of these new features, request a demo.

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Feature Preview: April Fools - The Making of GhostieBot

Co-Authors include: Austin Price & Jen Dooley

Introducing GhostieBot

For April Fools this year, the GreyNoise team created GhostieBot, an Artificial Unintelligence bot serving you all the answers you didn’t need. 

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We had a lot of fun creating it and thought it was a good example of the ideation, design, development, and release process at GreyNoise. Here we hope to walk you through that process so you can understand a little better how we work.

The Process

Ideation

We knew we wanted to have a fun April Fools joke this year, but everyone was already working on a ton of projects to make GreyNoise a more useful product. We decided to take a group of volunteers and just grab an hour here or there to work the problem.

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GreyNoise April Fools Tributes

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Our first stop was a Figma brainstorming session. Just set up some space for everyone to jot down ideas, start a 5-10 minute timer, play some smooth jazz, and go to work.

Brainstorming

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After all our ideas were gathered, we discussed them and added +1s to the ideas we liked. Since the world has been taken over by chatbots and large language models, we ultimately ended up with a GreyNoise chatbot that we could use to make jokes and expose some of the other ideas from the brainstorming session that weren’t big enough for their own show. Though you never know, the Internet Weather Report from the brainstorming session might pop up sometime…

Mocks

Next up, we had to create some mocks for what we wanted the GhostieBot interface to look like. Chatbots and messaging interfaces, in general, have some pretty established patterns. To keep things as simple and quick as possible, we leaned heavily on our design system and went with a standard chat/messaging layout. There were a few new elements in the design, like the message bubbles and Ghostie avatar, that we needed to create. We also needed to make sure it was responsive and handled small and large screens well. Altogether, these were pretty simple items, and we were able to have the finished mockups ready in under an hour.

Sourcing Responses

Since our chatbot is not a real chatbot, we had to actually come up with the responses we wanted, arguably a tougher task than creating a real chatbot. Luckily, we have a ton of nerds on staff who like terrible jokes. After spinning up a quick Notion page, we were able to crowdsource some ideas.

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Bad joke central

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Making it real

Now it is time to make it all real; we took the mock-ups, created a new page, and started building. We compiled the list of questions and properly formatted them for display. Then built out the basic structure of a chat interface; once that was set up, we added a few nice to haves:

  • “Enter” to submit instead of having to click “Submit”
  • Scroll offscreen gradient to add visual cues
  • Improved message timing so it felt like you were actually chatting with someone instead of instant replies.
  • “Ghosty is typing…” message based on response length

Once the interface was completed, we hid the Chat behind a feature flag as well as set a date window for the chat to be available to the public. This allowed us to test the chat before it went live.

And while we went with a more informative page for 127.0.0.1, y’all almost ended up with:

Alternate GreyNoise Localhost Details

Recap

We had a ton of fun putting this all together, and we hope you enjoyed it too. To keep in touch with GreyNoise as we figure out how to build an amazing product for the cyber security community, sign up for a free account (https://viz.greynoise.io/signup), join our Slack community (greynoiseintel.slack.com) and follow us on Twitter https://twitter.com/GreyNoiseIO. We also have a couple of positions open (https://www.greynoise.io/careers#Current-Openings).

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GreyNoise Voluntary Product Accessibility Template

At GreyNoise, we're excited to announce that our Voluntary Product Accessibility Template (VPAT) is now available. We believe that everyone should have equal access to our product and service, regardless of their disabilities or abilities. By providing a document that evaluates our product's accessibility for people with disabilities, we are taking a step forward in ensuring that our product meets the needs of all users. We are committed to creating an environment that is inclusive and accessible to everyone, and we believe that our VPAT is an essential part of this initiative.

What is a VPAT?

VPAT stands for Voluntary Product Accessibility Template, which is a document that outlines how accessible a product or service is to individuals with disabilities. It provides information on how well the product or service conforms to the Web Content Accessibility Guidelines (WCAG) and other accessibility standards. It's an important tool for ensuring that everyone, regardless of their abilities, can use and benefit from our product and service.

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What does a VPAT contain?

A VPAT is a detailed report on how well a product or service conforms to accessibility guidelines such as Section 508 of the Rehabilitation Act in the United States. It typically contains information on the product's conformance to accessibility standards, including how it complies with various criteria related to accessibility, such as keyboard accessibility, color contrast, and assistive technology compatibility. Additionally, the VPAT provides details on any known limitations or barriers that may exist for users with disabilities and any plans for future development or improvement.

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Why is a VPAT important?

Accessibility is a fundamental human right, and it's crucial that our product and service are designed with everyone in mind. People with disabilities make up a significant portion of the population and deserve equal access to information and services. A VPAT is a valuable tool for organizations to demonstrate their commitment to creating and providing accessible products and services, as well as fulfilling legal obligations. By completing a VPAT, we're ensuring that GreyNoise is accessible to as many people as possible.

Why is accessibility important?

Accessibility is important because it ensures that everyone, regardless of their abilities or disabilities, can access and use our platform. In the United States, approximately 61 million adults have a disability*, representing a significant portion of the population. By making our platform accessible, we're opening up our product and service to a much broader audience, leading to increased engagement, more meaningful interactions, and, ultimately, better outcomes for everyone.

In addition, accessibility can lead to better user experiences. People with disabilities may face significant challenges when accessing websites or online tools not designed with their needs in mind. By making our platform accessible, we're reducing these barriers and making it easier for everyone to use our product and service. 

What's next for GreyNoise's accessibility efforts?

At GreyNoise, we're committed to continuous improvement. We're constantly looking for ways to make our platform more accessible and inclusive. In addition to providing a VPAT, we're also working on other accessibility initiatives, such as improving our keyboard navigation, adding alternative text to images, and ensuring that we meet accessibility standards.

We believe that accessibility is an essential part of our platform, and we're committed to making our tools and services accessible to everyone. By providing a VPAT, we demonstrate our commitment to accessibility and inclusivity, which can lead to a better experience and outcomes for everyone. We look forward to continuing our accessibility efforts and making GreyNoise a platform everyone can use and enjoy. 

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Reference:

*https://www.inclusivecitymaker.com/disability-statistics-in-the-us/#:~:text=As%20stated%2C%20according%20to%20the,or%201%20in%204%20adults.

https://www.section508.gov/sell/vpat/

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7 benefits of a GreyNoise paid plan

(And when you should stick with our free version)

Giving back to the cyber security community will always be a key part of the GreyNoise mission, so our free plan isn’t going anywhere. 

But there are a lot of benefits to a paid plan that may not be immediately obvious (benefits other than subsidizing Andrew’s tweets). Let’s dig into the top 7 reasons you should upgrade, and when a paid plan might not be a good fit for you. 

Increased Search limits

The most obvious reason for a user to upgrade from free to paid is the expanded Search limits. Search is at the core of our product, it’s the first thing users see when they land on our visualizer and the primary way most users interact with GreyNoise. Asking GreyNoise for data on an IP, a CVE, a tag, or a trend all counts as a Search. 

The Free limits are designed for hobbyists, independent users, or for someone who is just starting to explore the GreyNoise ecosystem. They aren’t high enough to tap into automation or large scale data enrichment. So if you’re a team who wants to save time by throwing out all the hay to get to the needles faster, a paid plan will give you the volume you need. 

Increased limits on alerts and dynamic blocklists

In addition to Search, all paid customers get increased limits for alerts and dynamic blocklists - the other two features that make up the core of the GreyNoise product. 

Alerts let you configure an email notification that will trigger anytime the response to a GreyNoise Query Language (GNQL) query changes. Use them to identify compromised devices on your network (or a vendor or third party supplier’s network), or get a heads up when attackers start exploiting a vulnerability in the wild. 

Dynamic blocklists give you a full list of IPs associated with a GreyNoise tag. The list is updated hourly, and can be plugged directly into your next gen firewall to keep your perimeter safe. When the next Log4j happens, you can use a dynamic blocklist to buy your team needed time to patch. 

A more robust API with full IP context

The Community API has 1 endpoint, it takes an IP and returns a simple response with some basic information about that IP. Is the IP in the GreyNoise Noise or RIOT datasets? What is its classification? And a link to the visualizer.

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For some teams this is enough. But for teams that are stretched thin and need comprehensive answers fast, rely on automation to make their lives easier, or want to run more complex queries (like pulling back a list of IPs tagged with a specific CVE) access to our Enterprise API is a must. 

Our Enterprise API has 16 endpoints. Enterprise API users can: 

  • Get abbreviated IP info or full context (on up to 1,000 IPs in a single request)
  • Run full GNQL queries 
  • Get tag metadata
  • Check an IP against our RIOT dataset (a list of IPs known to be associated with common vendors)
  • Access our IP Similarity endpoints 
  • Access our IP Timeline endpoints

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A full list of our Enterprise API endpoints

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An example of a full context response, the response for this IP is 132 lines and includes full metadata, ports scanned, web paths and user agents, and fingerprints.

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More integrations, and expanded integration options

We have 31 integrations that support using a Community API key. But these integrations are limited by what the Community API can return, so if you need full context on the IP (which most users do) you'll have to click into the Visualizer to get a full picture.

Full integrations and integration with some of the most popular security tools like Splunk, QRadar, LogStash, and Recorded Future are available to paid customers. You’ll also want the higher Search limits that come with our paid plans to maximize our integrations and automate more of your work.

For a full list of integrations check out the GreyNoise docs.

Exclusive paid features

While limited access to the core GreyNoise features will always be available to free users, there are a handful of features that are only available to Paid customers, with more being added this year. These features can be used for enhanced enrichment, threat hunting, and protecting your perimeter from mass exploitation. 

Premium data fields

Premium data fields like our IP Destination fields tell users even more about what an IP is doing on the internet, and open up new Search queries. IP Destination specifically tells users which countries our sensors observed an IP scanning, and let users narrow down their searches to geo-targeted traffic. All paid plans come with IP Destination. 

Export

Getting data out of the visualizer (or accessing full context in the API) is restricted to paying customers. You can export GNQL search results or analysis results to a CSV or JSON file. 

IP Timeline

IP Timeline lets security analysts and threat hunters look back at an IP’s behavior over time. Answer the question, “what was this IP doing 7 days ago?” Useful if you find an IP in your logs and want to know what it was doing the day it hit your system. 

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Use our IP Timeline feature to understand how an IP’s behavior changes over time. 

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IP Similarity

IP Similarity helps users identify potential actors and infrastructure associated with an IP you’re investigating. All users can see how many IPs GreyNoise has identified as similar to a given IP, but only paying customers can access the list of similar IPs and a breakdown of the factors that determine similarity. 

Use our IP Similarity feature to identify potential actors or infrastructure amongst internet scan data.

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Feeds

Feeds are a useful way to enrich your existing data without blowing up your Search limit, or to narrow down a search into a big dataset. 

Enterprise support

Paying customers get direct access to our Customer Success team who have a deep knowledge of the GreyNoise product, integrations, and customer use cases. While we will always do our best to support all of our users, our Customer Success team goes above and beyond for our customers with onboarding, training sessions, and quarterly check-ins.

Convenience

One of the most important benefits of a paid plan is convenience, and our best customers get this. You’re strapped for time. You’re trying to keep up with changing tactics from the bad guys, training and hiring good analysts, and the latest demands from the rest of your org. Any time you can save has real value. 

GreyNoise has proven time and time again that we save our paying customers time, and generate a pretty significant ROI. 

Upgrade to a paid plan if…

There’s a lot of value unlocked when you move from a Free GreyNoise account to one of our paid plans. You probably want to upgrade if you fit into one or more of these buckets.

  • You have a mid-size or large team heavily leveraging the visualizer for manual alert triage 
  • You want to build automations or enrichments leveraging GreyNoise data into your workflows
  • You’re using Splunk, QRadar, Panther or one of the other tools supported by our paid integrations
  • You want an easy way to monitor large blocks of IP space for malicious behavior
  • You want to block IPs scanning for emerging threats from touching your perimeter entirely
  • You are doing advanced threat hunting 
  • You want to leverage GreyNoise data in your product or service
  • You need enterprise support
  • You value saving your analysts time anywhere you can

A GreyNoise paid plan isn’t necessary for everyone, we get that. Don’t worry about a paid plan right now if you fit into one of these buckets:

Your team has a manageable number of alerts

Look, if you’re a team of 1 or 2 analysts, and you can easily handle all of the perimeter-related alerts in your SIEM then you’re probably not going to get a ton of benefit from a GreyNoise subscription right now. You can always create a free account, and use it as needed when you have questions about a strange IP or hot, new CVE. 

You outsource your security program

If most or all of your security program is managed by MSSP/MDR partners, they can leverage GreyNoise on your behalf to provide you a better service more cost-efficiently. Some of our rockstar MSSP/MDR partners include:

You’re a student, academic, or independent researcher

If you’re a student, academic, or an independent researcher using GreyNoise for non-commercial purposes then you may actually qualify for our VIP program. VIP users get access to all of the same features and benefits as paying customers, at no cost. 

Check out our pricing to learn more

In the end it’s up to you. GreyNoise isn’t going to be a good fit for everyone, and that’s okay. You can always use GreyNoise for free, and reach out later when your security team has grown. But if these benefits resonated with you, then consider reaching out to our sales team. They’re here to help, not be pushy, and know a ton about GreyNoise. 

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Introducing IP Timeline

When running across an unknown IP address in the logs, the first move might be to check the IP address’s reputation through a number of services.  This check is useful for the immediate task at hand, but what if you could see not only reputation reports but see, at a granular level, when and what is causing this reputation?  That’s where GreyNoise comes in. 

Alongside the common fields of a GreyNoise IP address page’s located in the Visualizer (which include relevant DNS information, destination sites, and other data), GreyNoise now has a feature called the IP Timeline. The IP Timeline displays activity as seen by GreyNoise sensors of a particular IP Address over the past thirty days.  Let’s take a look at an IP address and explore this tool further.

Getting Started – IP address page

When an IP address is entered into the GreyNoise search box, if GreyNoise has observed scan activity from the IP, you will receive an IP Address page detailing data and related tags:

In this example (IP address 41.65.223.220), an opportunistic scanner appears to be crawling for SMBv1 endpoints and trying to brute force MSSQL servers.

Within the fields displayed are which ports this address scans, any associated fingerprints and what kinds of web requests the IP is known to make. In this case, GreyNoise does not have a lot of fingerprint and request data. So, how can we know for sure that this IP address is still active and malicious?

This is where the IP Timeline feature comes into play.  Next to the summary of the IP address, there’s a tab labeled ‘timeline’.  Let’s click that and see what we find:

Voila!  The page has gone from an overview of the IP address to discrete data points showing when, exactly, GreyNoise has noticed activity.  Consecutive days of the same activity are connected by a line.

Each data point GreyNoise has for the IP address is a field along the Y axis, and each day that GreyNoise notices it is the X axis. You can see respective fields and dates along the left and top sides of the graph.  In this example, you can see that on the 1st of January there is SMBv1 crawling observed.  Then, on the 2nd, there’s MSSQL brute force attempts. The SMBv1 crawling has an unknown intention so it’s listed as white, while the MSSQL brute force attempts are highlighted in red as they are tagged as malicious activity.

How is this useful?

This graph can be used for more than just a quick check on an IP address.  For example: you are running an MSSQL server and found this IP address in your logs. Seeing somebody trying to brute force your server can be a nerve-wracking experience!  However, by checking this graph you can see that this address attempts to brute force every 8 days on the dot, implying an automated process. That’s still not great, but it’s less scary than a concerted human effort. From there, you could make the call to block at the firewall or you could make sure your passwords aren’t on any well-known word lists and continue to observe the IP address.

Additionally, if you are looking for behavior patterns on an IP address, this graph could come in handy.  In this example, we only see two cases where the IP address crawls SMBv1 and then attempts to brute force the next day but, if this was a consistent pattern, this may be indicative of a pattern used when deciding which hosts to try and brute force. You could then use that information to pivot into checking your SMB logs for anything suspicious.

Final Takeaways

GreyNoise is always looking for new ways to bring as much value as possible.  IP Timeline data is only one part of a much bigger ecosystem you can integrate into your processes and investigations. Try it out yourself by signing up for our *enterprise trial or contact us to schedule a more in depth demo.

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(*Create a free GreyNoise account to begin your enterprise trial. Activation button is on your Account Plan Details page.)

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Introducing IP Geo Destination

Why We Created IP Geo Destination 

If you’ve ever heard our founder and CEO, Andrew Morris, speak, you’ll know that one of the core reasons GreyNoise exists is to answer the question “Is everyone seeing this, or is it just me?” 

GreyNoise provides details about opportunistic scan activity by source IP as observed across our sensor network. When large geopolitical events happen, like the ongoing Russia-Ukraine war, our research team historically has been able to provide details on the destination of the traffic we’re seeing as well (e.g. Russian scans and exploitation attempts only focusing on our Ukrainian sensors). We are proud to share that this capability, labeled as IP Geo Destination, is now available to all GreyNoise customers via the Visualizer and API endpoints as of today.

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What IP Geo Destination Can Show You

Using the new IP Geo Destination feature, we can delve deeper into anomalies in scanning traffic.

Multi-Destination Results

Recently, there has been an uptick in scan activity related to scanning for DB2 databases as highlighted by the trends page. Using this as a starting point organizations can begin to investigate further to better understand why there is a sudden increase in scan activity.

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DB2 Scanner Tag observes irregular traffic patterns. Source: GreyNoise

Using the GreyNoise command line tool, we can search ‘.metadata.destination_countries’ to derive where this activity is pointing to. The traffic seen from the DB2 Scanner in the last 7 days reveals an even distribution of traffic across GreyNoise sensors in 41 different countries (see our docs for a list of all countries where we have sensors today).

Distribution of destination countries for the previous 7 days of activity for the DB2 Scanner tag. Source: GreyNoise

Further investigating IPs active in the last seven days that are scanning for DB2 instances shows that all of them have been tagged as malicious in GreyNoise. Most of them have multiple tags associated with each IP address, several of which are related to various worms attempting to propagate across the systems connected to the internet. 

Overview of the previous 7 days of activity and classification for IP’s tagged as a DB2 scanner. Source: GreyNoise

Single Destination Results 

Threat hunters looking for more targeted activity can add the `single_destination` parameter to identify IPs focusing on a particular geographic region.

Filtering down results to look for IPs that are targeting a specific country. Source GreyNoise

In the example above, by entering the search `tags:"DB2 Scanner" destination_country:Ukraine single_destination:true `, you can filter results to show only activity that is targeting a single country, in this case, Ukraine. Defenders that work for the government, non-profit organizations, or are generally interested in a specific country or region can utilize this to focus on localized activities and potential threats.

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With the additional data provided by IP Geo Destination, GreyNoise users can better understand how attacks impact different geographic regions. Our destination data is built off of our own sensor network so the geographic information being provided is first-hand. This feature is designed for cyber defenders to connect geopolitical motivations with scan and attack traffic and help responders quickly prioritize and triage alerts.

If you have questions about this feature or are interested in getting a demo contact our sales team.

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New features - anomaly and trend detection

Feature explainer: anomaly and trend detection

Defenders have a remarkably tough job. They must understand — to the largest extent possible — which event needs investigating right now. There are many triggers for such events, but a major one is knowing when their threat landscape has changed. More specifically, defenders need to know when traffic (and actor) behavior has changed sufficiently to warrant taking notice or action.

Change detection comes in many forms. One such form comes under the lofty heading of "anomaly detection," which may also be referred to as "trend detection." Most modern detection and response solutions have some sort of anomaly detection capability.

GreyNoise has recently introduced a new trend detection feature in our platform that will help inform both researchers and organization defenders about potentially new or dangerous traffic behavior changes as quickly as possible. This gives researchers and defenders the necessary context to decide if further action is warranted.

Background on trends and anomalies

Our new Anomaly/Trend Detection feature operates on Tags, GreyNoise’s automated event labeling system. Our processing takes signatures developed by our Research team and applies tags to the packet traffic from our sensor network. These tags are used to add context from actor attribution to behavior, including scanning, crawling, or exploitation events. Each one represents a particular kind of traffic: malicious, benign, or as yet unknown. Each can also encompass one or more protocols, vulnerabilities, and/or exploits.

Monitoring tag behavior over time is a large part of GreyNoise’s value. Because we see how many sensors are hit with traffic events labeled with a particular tag every hour, we can assess which tags are becoming more popular, which ones are experiencing a near-term anomaly in traffic (possibly a notable event in itself), and which are going quiet. At GreyNoise, we look for opportunities to filter out the noise. Traffic that trends upward or exhibits an anomalous "spike" is noteworthy because it is "noisy.”

How it works

Detecting trends and anomalies is about finding deviation from previous behavior, particularly in a positive direction. Both tasks start with finding the average over a long period, at least ten days. The Trends tab looks at slower increases in traffic for a specific tag, comparing the long-term average to a short-term, more recent average, and doing the classic percent-change formula. This produces a value we can use to rank which tags are seeing the largest increase in average traffic.

Immediately above is one example of “trending” behavior.

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Detecting an anomaly (as seen immediately above) is somewhat trickier, as we’re not interested in alerting on every recent anomaly. Indeed, it’s not inconceivable that a “quiet” tag that’s gone unseen for a while could suddenly start appearing intermittently (see below). That tag could very well get a separate report for each anomaly, even if each anomaly is not all that tall compared to its neighbors. 

We have to find a single recent peak, and preferably the highest. We do so with two algorithms: first, we use a moving window to determine which sample(s) have the largest (positive) deviation from the average value for that window. Second, we check for a change in slope, as a peak signifies a change from increasing to decreasing behavior. Between the two algorithms, we can find peaks reliably, accurately, and precisely. The peak values are then subjected to the percent change formula, so we can compare anomalies and trends for each tag.

Ranking the output of these algorithms, we present the tags that have the largest recent increase in trend as well as the tallest recent peak, both relative to previous average behavior. 

What to do about it

Loading up our Tag Trends page, you’ll see trending tags and anomalies: lists of the tags exhibiting each of the behaviors the strongest out of our vast collection of known tags.

Trending tags are showing a marked increase in average traffic; that is, the average now is relatively greater than previously. This could continue over time, suggesting the possibility of the related vulnerabilities being more commonly exploited (or at the very least, more commonly seen in data from one’s inbound internet security perimeter). This raises the odds of seeing it on our customer’s own perimeter, and therefore increases the urgency for monitoring in more detail and patching, if possible.

Anomalies in a tag manifest sudden jumps in behavior–and could be more useful to see what already happened than for projection about future behavior. Anomalies, by our internal definition, have already started to ebb, so the real “peak” has passed. With the largest anomalies listed, though, we can note the timing of large events/incidents that may illuminate what happened and how. However, it is possible that repeated anomalies could signal a new behavior pattern of intermittent bursts of activity: then the timing between those anomalies could show coordination, how many groups are involved, or even in which time zones they likely operate. 

What is particularly powerful is the ability to raise the conversation around tags (and therefore particular exploit vectors) as soon as they’re seen in numbers “in the wild,” instead of waiting for a particular exploit to hit the news. Additionally, each tag notes a particular approach. So, if a product has multiple potential exploits one could patch for, the tag (or tags) that are seeing the most traffic should be patched soonest.

All this being said, of course, these behaviors may not be seen on your perimeter. You may load the Tag Trends page and find that none of the “trending” tags are increasing their traffic for you, and you may be seeing traffic on other vectors. This is perfectly normal, and likely indicates that your firewall is doing its job, or that your attack surface is minimized to the threats and activity on the web at large. You may also be investigating a sudden wave of traffic of a particular type, and see that it didn’t make our Anomalies list. This means that, likely as not, your wave of traffic is more targeted than it may appear at first, and perhaps some caution may be warranted.

A note on data over time

There’s been some talk in the last few paragraphs about possibilities because this is largely cutting-edge research in cybersecurity. Already, we have seen tags which saw a drop in behavior that appear to be trending (as said drop passes out of the recent time window). The movement of the drop drags down the previous baseline, which makes the resumption of normal activity look like it’s trending to the algorithm. Perhaps it’s not trending upward from where it started, but the whole sample still exhibits notable behavior; sometimes the resumption of normal behavior out-trends the weaker actual “trending” tags. Notable behavior is notable behavior. 

There are more exotic patterns lurking in the time series data that our researchers already know and recognize. For us, it’s a matter of building a statistical system around that recognition so we can further automate. No one knows all of what’s possible out there, but we’re listening, so we know better than many. As soon as GreyNoise finds something new, you can rest assured that our findings make their way into refining this feature and other features to come.

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Defending Against Emerging Threats with GreyNoise Investigate 4.0

New GreyNoise Trends dashboard helps security analysts identify and respond to opportunistic “exploit” attacks

The increasing frequency of internet-wide exploit attacks targeting newly announced vulnerabilities is a tremendous challenge for security teams. There is a long line of “celebrity vulnerabilities” that we at GreyNoise have observed with increasing alarm. And given our focus on internet noise, customers have naturally been asking for our help in providing visibility into vulnerabilities being actively exploited in the wild.

This is why we created GreyNoise Trends, a new view into the GreyNoise data set to help security analysts identify and respond to internet attacks targeting specific vulnerabilities.

New Vulnerabilities Create A Race Against Time for Security Teams

When a new vulnerability is discovered and announced, it's a race against time to see who can find vulnerable servers first. For example, when the Apache Log4j vulnerability (CVE-2021-44228, aka “Log4Shell”) was announced on December 5, 2021, GreyNoise saw a dramatic spike in internet-wide scanning activity searching for servers that exposed this vulnerability:

Figure: Log4Shell Unique IPs per hour, Source: GreyNoise Research

Note that thousands of unique IP addresses searching for a vulnerability can generate billions or trillions of connection requests across the internet, generating a storm of internet noise that makes it difficult to identify true threats.

For security teams, responding to this kind of event is extremely challenging. Under pressure of a newly announced vulnerability, they need to understand how serious the vulnerability is, whether it is being actively exploited in the wild, whether they are vulnerable, and whether they may have already been compromised. And if they have vulnerable systems, they need to patch them on an emergency basis.

Vulnerability Exploits Used in 34% of Cyber Attacks in 2021

According to a recent report by IBM, severe vulnerabilities in internet-facing enterprise software are being exploited and weaponized at a higher frequency, at massive scale:

  • 34% of attacks in 2021 used vulnerability exploitation - opportunistic “scan-and-exploit” attacks are quickly approaching phishing as the most-used cyber attack vector, with 34% of attacks leveraging vulnerabilities, compared to 41% of attacks leveraging phishing.
  • Vulnerability exploit attacks grew 33% year over year in 2021 - the number of incidents that were caused by vulnerability exploitation this past year rose 33% from 2020, indicating this attack vector’s stronghold in threat actors’ arsenals.

Furthermore, the amount of time between disclosure of a new vulnerability and the start of active exploitation has been reduced to a matter of hours, leaving defenders with less time to react and respond.

GreyNoise Investigate - Real-Time Visibility and Blocking of Exploit Attacks

GreyNoise Investigate helps security analysts identify and respond to opportunistic “scan-and-exploit” attacks, providing context about the behavior and intent of IP addresses scanning the internet. Investigate allows security teams to:

  • Quickly triage alerts based on malicious, benign, or targeted classifications
  • Identify trending internet attacks targeting specific vulnerabilities and CVEs
  • Block and hunt for IP addresses opportunistically attacking a specific vulnerability

With the release of Investigate 4.0, GreyNoise has created a new Trends page that helps security analysts identify and respond to internet attacks targeting specific vulnerabilities. This new page provides two key capabilities:

  • Attack Trend Visibility - the Trends graph shows the number of IP addresses targeting a specific vulnerability or CVE over time. This unique visualization allows security teams to identify and prioritize internet threats based on how actively a vulnerability is being exploited in the wild.
  • Dynamic IP lists - the new Trends page provides several ways for analysts to access a dynamic list of IP addresses actively scanning for a vulnerability in the past 24 hours. This data can be used to provide near-term protection by blocking attacks at the firewall or WAF, as well as providing indicators of compromise to use to hunt for potentially compromised systems.

Taken together, this new Trends functionality allows security teams to quickly understand if a vulnerability is relevant to their organization, and buys them the time they need to put security defenses in place.


Figure: GreyNoise Investigate 4.0 showing Attack Trends graph for the Apache Log4j vulnerability (CVE CVE-2021-44228)

GreyNoise Trends for Community Accounts

Note that GreyNoise continues to be committed to supporting the broader security community via our free Community plan, and this new GreyNoise Trends functionality is included. Community members will be able to subscribe to a single tag to export the Dynamic IP list.

In addition, for severe vulnerabilities with global impact, GreyNoise will selectively make the full functionality of the paid Trends page available to ANYONE who wants to take advantage of it, including both attack visibility and dynamic IP lists.

Try GreyNoise Trends For Yourself, And Tell Us What You Think

One important note about GreyNoise Trends - we’ve launched this new capability as Beta code for several reasons:

  • Potential bugs and stability - We made the decision to build and launch this new capability after analyzing our experience during the Apache Log4j vulnerability event in late December. Over the past two months, our engineering team has been working hard to build out this new functionality. If you notice any issues or have questions about functionality, please do not hesitate to reach out to our team: support@greynoise.io
  • Learning - We realize that we need to learn more about how analysts and others will use this new, never-before-seen functionality. We’ve made our best guess about how to package this functionality into our Community and Investigate plans, but we know there are things we don’t know.
  • Roadmap - Finally, we have a number of ideas about where we think we should take this capability in the future, but we need your help and guidance to shape this direction. To this end, we hosted a “futures'' discussion at our 3rd Open Forum on March 17, 2022.

So please, sign up for a free GreyNoise Community account if you don’t already have one, try out GreyNoise Trends, and let us know what you think. And to get you started, here are a few interesting Trends pages to check out:

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