CB detecting-lateral-movement-in-network
Identifies lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek, Velociraptor, and SIEM correlation rules to detect attackers moving between systems.
Identifies lateral movement techniques in enterprise networks by analyzing authentication logs, network flows, SMB traffic, and RDP sessions using Zeek…
As a process B 71/100 · Nearly there — weak spots: failures and branches, running it twice
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 11
✓ No critical or high findings
Medium and low: 11
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medium Dangerous commands
cmd-privilegeSKILL.md:215Privilege escalation / world-writable permissionssudo tee /opt/zeek/share/zeek/site/custom-detections/lateral-movement.zeek << 'ZEEKEOF'
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low Risky intent
intent-offensive-securityreferences/api-reference.md:1Offensive-security / dual-use content (legitimate for authorised testing; review intended use)# Lateral Movement Detection API Reference
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low Risky intent
intent-offensive-securityreferences/api-reference.md:3Offensive-security / dual-use content (legitimate for authorised testing; review intended use)## Windows Event IDs for Lateral Movement
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low Risky intent
intent-offensive-securityreferences/api-reference.md:17Offensive-security / dual-use content (legitimate for authorised testing; review intended use)## Zeek Log Files for Lateral Movement
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low Risky intent
intent-offensive-securityreferences/api-reference.md:29Offensive-security / dual-use content (legitimate for authorised testing; review intended use)## Zeek Script - Lateral Movement Detection
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low Risky intent
intent-offensive-securityreferences/api-reference.md:45Offensive-security / dual-use content (legitimate for authorised testing; review intended use)## Splunk SPL - Lateral Movement Queries
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low Risky intent
intent-offensive-securitySKILL.md:3Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)description: 'Identifies lateral movement techniques in enterprise networks by analyzing
detector -
low Risky intent
intent-offensive-securitySKILL.md:37Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)# Detecting Lateral Movement in Network
detector -
low Risky intent
intent-offensive-securitySKILL.md:41Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- Monitoring enterprise networks for post-compromise lateral movement patterns (pass-the-hash, RDP hopping, PSExec)
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low Risky intent
intent-offensive-securitySKILL.md:42Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)- Building SIEM detection rules and alerts for common MITRE ATT&CK lateral movement techniques (T1021, T1570)
detector -
low Risky intent
intent-offensive-securitySKILL.md:45Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- Validating that network segmentation and access controls effectively limit lateral movement paths
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "domain" - note
frontmatter-keyunknown frontmatter key "subdomain" - note
frontmatter-keyunknown frontmatter key "d3fend_techniques" - note
frontmatter-keyunknown frontmatter key "nist_csf" - note
frontmatter-keyunknown frontmatter key "mitre_attack"
Process rating: all ten parameters 71/100
- 0Failures and branches. Linear process with no failure handling
- 30Running it twice. 2 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 4062 tokens
- 100Tools and files. No external tools needed
- 100Steps. 26 steps
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- -41 reference files, but SKILL.md never points to them: the model will not open them
- -31 of 1 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 237: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 26 items
- +3Output format is stated explicitly
- +4Has examples (8 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.