CC performing-threat-hunting-with-elastic-siem
Performs proactive threat hunting in Elastic Security SIEM using KQL/EQL queries, detection rules, and Timeline investigation to identify threats that evade automated detection. Use when SOC teams need to hunt for specific ATT&CK techniques, investigate anomalous behaviors, or validate detection coverage gaps using Elasticsearch and Kibana Security.
Performs proactive threat hunting in Elastic Security SIEM using KQL/EQL queries, detection rules, and Timeline investigation to identify threats that evade…
As a process C 63/100 · Has gaps — weak spots: failures and branches, running it twice, progress reporting
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 · 7
✓ No critical or high findings
Medium and low: 7
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low Risky intent
intent-offensive-securityreferences/api-reference.md:5Offensive-security / dual-use content (legitimate for authorised testing; review intended use)Performs proactive threat hunting against Elasticsearch indices using structured queries for LOLBin abuse, credential dumping, lateral movement, and persistence mechanisms mapped to MITRE ATT&CK.
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low Risky intent
intent-offensive-securityreferences/api-reference.md:27Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- **ATT&CK**: T1003 (OS Credential Dumping)
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low Risky intent
intent-offensive-securitySKILL.md:57Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- Red team exercises reveal detection gaps that need hunting query development
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low Risky intent
intent-offensive-securitySKILL.md:121Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)**Detect credential dumping sequence (T1003):**
detector -
low Risky intent
intent-offensive-securitySKILL.md:132Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)**Detect lateral movement via PsExec (T1021.002):**
detector -
low Risky intent
intent-offensive-securitySKILL.md:173Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)"name": "Command and Control"
quoted
A further 1 matches are quotations in this security skill's documentation and are not counted as findings.
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 "nist_ai_rmf" - note
frontmatter-keyunknown frontmatter key "atlas_techniques" - 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 63/100
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 5 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 30 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2203 tokens
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 351: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 30 items
- +3Output format is stated explicitly
- +4Has examples (11 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.