BB performing-deception-technology-deployment
Deploys deception technology including honeypots, honeytokens, and decoy systems to detect attackers who have bypassed perimeter defenses, providing high-fidelity alerts with near-zero false positive rates. Use when SOC teams need early warning of lateral movement, credential abuse, or internal reconnaissance by deploying convincing traps across the network.
Deploys deception technology including honeypots, honeytokens, and decoy systems to detect attackers who have bypassed perimeter defenses, providing…
As a process B 70/100 · Nearly there — weak spots: failures and branches, running it twice, progress reporting
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 · 5
✓ No critical or high findings
Medium and low: 5
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low Risky intent
intent-offensive-securitySKILL.md:6Offensive-security / dual-use content (legitimate for authorised testing; review intended use)of lateral movement, credential abuse, or internal reconnaissance by deploying convincing
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low Risky intent
intent-offensive-securitySKILL.md:40Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)- SOC teams need high-fidelity detection of post-compromise lateral movement with near-zero false positives
detector -
low Risky intent
intent-offensive-securitySKILL.md:71Offensive-security / dual-use content (legitimate for authorised testing; review intended use)Cloud (AWS VPC) Canary EC2 + S3 Cloud lateral movement detection
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low Risky intent
intent-offensive-securitySKILL.md:149Offensive-security / dual-use content (legitimate for authorised testing; review intended use)# (Mimikatz/credential dumping will find these)
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low Risky intent
intent-offensive-securitySKILL.md:279Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- **Lateral Movement Detection**: Attacker enumerates SMB shares and accesses honeypot file server — immediate high-fidelity alert
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_csf" - note
frontmatter-keyunknown frontmatter key "mitre_attack"
Process rating: all ten parameters 70/100
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 7 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
- 100Tools and files. No external tools needed
- 100Steps. 24 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2614 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 360: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 24 items
- +3Output format is stated explicitly
- +4Has examples (10 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.