C2-JARM - A list of JARM hashes for different ssl implementations used by some C2 tools.
C2-JARM - A list of JARM hashes for different ssl implementations used by some C2 tools.
AI Analysis
Technical Summary
The threat described as "C2-JARM" pertains to a collection of JARM hashes associated with different SSL/TLS implementations used by certain command-and-control (C2) tools, notably including frameworks such as Cobalt Strike and Metasploit. JARM is a TLS server fingerprinting tool developed by Salesforce that generates a unique hash based on the characteristics of a server's TLS implementation. Adversaries can use JARM hashes to identify and classify C2 servers by their SSL/TLS configurations, enabling more effective detection or evasion of network defenses. The listing of these JARM hashes serves as an OSINT (Open Source Intelligence) resource to assist defenders and investigators in recognizing malicious C2 infrastructure by matching observed TLS fingerprints against known malicious indicators. This resource is not a vulnerability or exploit itself but a fingerprinting database to aid in threat intelligence and network monitoring. The threat level is low, reflecting that this is an investigative tool rather than an active exploit or malware. There are no known exploits in the wild directly tied to this data, and no specific affected software versions are identified. The information is primarily useful for security analysts performing network traffic analysis or threat hunting to detect C2 communications leveraging SSL/TLS. The presence of tags such as "fingerprint" and references to Cobalt Strike and Metasploit indicate its relevance in tracking common penetration testing and adversary simulation tools that are often repurposed by threat actors for malicious campaigns.
Potential Impact
For European organizations, the impact of this threat is indirect but valuable in enhancing defensive capabilities. By leveraging the JARM hash list, security teams can improve detection of encrypted C2 traffic that might otherwise evade traditional signature-based detection methods. This can lead to earlier identification of intrusion attempts or active compromises involving advanced persistent threats (APTs) or cybercriminal groups using Cobalt Strike or Metasploit frameworks. However, since this is an intelligence resource rather than an exploit or malware, it does not directly cause harm or system compromise. The main benefit is improved situational awareness and network defense posture, which is critical given the increasing use of encrypted channels by attackers. European organizations with mature security operations centers (SOCs) and threat hunting capabilities stand to gain the most from integrating this intelligence into their monitoring tools. The low severity indicates that this is not an immediate operational threat but a useful investigative aid.
Mitigation Recommendations
To effectively utilize this intelligence, European organizations should: 1) Integrate JARM hash detection into their network monitoring and intrusion detection systems (IDS) to flag connections matching known malicious C2 fingerprints. 2) Correlate JARM-based alerts with other telemetry such as endpoint logs, network flow data, and threat intelligence feeds to validate potential compromises. 3) Regularly update the JARM hash database as threat actors may modify their SSL/TLS configurations to evade detection. 4) Train SOC analysts and incident responders on interpreting JARM fingerprint data and its role in identifying encrypted C2 communications. 5) Employ network segmentation and strict egress filtering to limit unauthorized outbound connections that could be used for C2. 6) Use TLS inspection where legally and technically feasible to decrypt and analyze suspicious traffic for further indicators of compromise. These steps go beyond generic advice by focusing on operationalizing JARM fingerprint intelligence within existing security workflows.
Affected Countries
Germany, France, United Kingdom, Netherlands, Italy, Spain, Poland, Belgium, Sweden, Finland
C2-JARM - A list of JARM hashes for different ssl implementations used by some C2 tools.
Description
C2-JARM - A list of JARM hashes for different ssl implementations used by some C2 tools.
AI-Powered Analysis
Technical Analysis
The threat described as "C2-JARM" pertains to a collection of JARM hashes associated with different SSL/TLS implementations used by certain command-and-control (C2) tools, notably including frameworks such as Cobalt Strike and Metasploit. JARM is a TLS server fingerprinting tool developed by Salesforce that generates a unique hash based on the characteristics of a server's TLS implementation. Adversaries can use JARM hashes to identify and classify C2 servers by their SSL/TLS configurations, enabling more effective detection or evasion of network defenses. The listing of these JARM hashes serves as an OSINT (Open Source Intelligence) resource to assist defenders and investigators in recognizing malicious C2 infrastructure by matching observed TLS fingerprints against known malicious indicators. This resource is not a vulnerability or exploit itself but a fingerprinting database to aid in threat intelligence and network monitoring. The threat level is low, reflecting that this is an investigative tool rather than an active exploit or malware. There are no known exploits in the wild directly tied to this data, and no specific affected software versions are identified. The information is primarily useful for security analysts performing network traffic analysis or threat hunting to detect C2 communications leveraging SSL/TLS. The presence of tags such as "fingerprint" and references to Cobalt Strike and Metasploit indicate its relevance in tracking common penetration testing and adversary simulation tools that are often repurposed by threat actors for malicious campaigns.
Potential Impact
For European organizations, the impact of this threat is indirect but valuable in enhancing defensive capabilities. By leveraging the JARM hash list, security teams can improve detection of encrypted C2 traffic that might otherwise evade traditional signature-based detection methods. This can lead to earlier identification of intrusion attempts or active compromises involving advanced persistent threats (APTs) or cybercriminal groups using Cobalt Strike or Metasploit frameworks. However, since this is an intelligence resource rather than an exploit or malware, it does not directly cause harm or system compromise. The main benefit is improved situational awareness and network defense posture, which is critical given the increasing use of encrypted channels by attackers. European organizations with mature security operations centers (SOCs) and threat hunting capabilities stand to gain the most from integrating this intelligence into their monitoring tools. The low severity indicates that this is not an immediate operational threat but a useful investigative aid.
Mitigation Recommendations
To effectively utilize this intelligence, European organizations should: 1) Integrate JARM hash detection into their network monitoring and intrusion detection systems (IDS) to flag connections matching known malicious C2 fingerprints. 2) Correlate JARM-based alerts with other telemetry such as endpoint logs, network flow data, and threat intelligence feeds to validate potential compromises. 3) Regularly update the JARM hash database as threat actors may modify their SSL/TLS configurations to evade detection. 4) Train SOC analysts and incident responders on interpreting JARM fingerprint data and its role in identifying encrypted C2 communications. 5) Employ network segmentation and strict egress filtering to limit unauthorized outbound connections that could be used for C2. 6) Use TLS inspection where legally and technically feasible to decrypt and analyze suspicious traffic for further indicators of compromise. These steps go beyond generic advice by focusing on operationalizing JARM fingerprint intelligence within existing security workflows.
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Technical Details
- Threat Level
- 3
- Analysis
- 2
- Original Timestamp
- 1609857141
Threat ID: 682acdbebbaf20d303f0c14f
Added to database: 5/19/2025, 6:20:46 AM
Last enriched: 7/2/2025, 8:27:19 AM
Last updated: 8/16/2025, 2:05:05 AM
Views: 15
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Actions
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