analyzing-linux-audit-logs-for-intrusion
Uses the Linux Audit framework (auditd) with ausearch and aureport utilities to detect intrusion attempts, unauthorized access, privilege escalation, and suspicious system activity. Covers audit rule configuration, log querying, timeline reconstruction, and integration with SIEM platforms. Activates for requests involving auditd analysis, Linux audit log investigation, ausearch queries, aureport summaries, or host-based intrusion detection on Linux.
74
92%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
Medium
Suggest reviewing before use
Security
1 medium severity finding. This skill can be installed but you should review these findings before use.
W013: Attempt to modify system services in skill instructions.
What this means
The skill prompts the agent to compromise the security or integrity of the user’s machine by modifying system-level services or configurations, such as obtaining elevated privileges, altering startup scripts, or changing system-wide settings.
Why it was flagged
The skill instructs the agent to perform multiple privileged system modifications (edit /etc/audit/rules.d, load auditctl/augenrules, change /etc/audit configs, adjust kernel audit settings and install/enable services), all of which require root/sudo and therefore change the host's state and security posture.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The required runtime workflow reads and parses the host’s audit log file `/var/log/audit/audit.log` (kernel-generated text that may include attacker-controlled command/file strings), which is then fed into the agent’s LLM context via the agent’s printed/JSON output.
- Repository
- mukul975/Anthropic-Cybersecurity-Skills
- Commit
9429fe9
- Audited
- Security analysis
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.