CD autonomous-red-teamer
AI-driven dynamic security fuzzing, exploit generation (XSS, SQLi, SSRF, Prompt Injection), and automated patch remediation / Fuzzing keamanan dinamis berbasis AI, eksploitasi, dan remediasi otomatis.
AI-driven dynamic security fuzzing, exploit generation (XSS, SQLi, SSRF, Prompt Injection), and automated patch remediation / Fuzzing keamanan dinamis…
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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
-
low Risky intent
intent-offensive-securitySKILL.md:49Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)describe('Red Team Security: Prompt Injection Guardrails', () => {quoted -
low Risky intent
intent-offensive-securitySKILL.md:82Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)describe('Red Team Security: SSRF Protection', () => {quoted -
low Risky intent
intent-offensive-securitySKILL.md:215Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)describe('Uji Keamanan Red Team: Pertahanan Prompt Injection', () => {quoted -
low Risky intent
intent-offensive-securitySKILL.md:245Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)describe('Uji Keamanan Red Team: Perlindungan SSRF', () => {quoted
A further 1 matches are quotations in this security skill's documentation and are not counted as findings.
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Unexpected scalar at node end at line 3, column 23: author: "Roedy Rustam" ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 38 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3090 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +3Description length 200: enough signal without eating the budget
- +4Structure: 27 headings
- +3Step-by-step instructions: 38 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.