Best for
- Scanning a repository for exploitable vulnerabilities
- Preparing a Huntr, HackerOne, or similar bounty submission
- Triage where the question is "does this actually pay?" rather than "is this theoretically unsafe?"
affaan-m/ECC/skills/security-bounty-hunter/SKILL.md
Hunt for exploitable, bounty-worthy security issues in repositories. Focuses on remotely reachable vulnerabilities that qualify for real reports instead of noisy local-only findings.
Decision brief
Use this when the goal is practical vulnerability discovery for responsible disclosure or bounty submission, not a broad best-practices review.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/affaan-m/ECC --skill "skills/security-bounty-hunter"Inspect the Agent Skill "security-bounty-hunter" from https://github.com/affaan-m/ECC/blob/4e973d3eaf92d97f8d2e2d8abb39d8bdc8711b38/skills/security-bounty-hunter/SKILL.md at commit 4e973d3eaf92d97f8d2e2d8abb39d8bdc8711b38. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
1. Check scope first: program rules, SECURITY.md, disclosure channel, and exclusions. 2. Find real entrypoints: HTTP handlers, uploads, background jobs, webhooks, parsers, and integration endpoints. 3. Run static tooling where it helps, but treat it as triage input only. 4. Read…
Scanning a repository for exploitable vulnerabilities
Bias toward remotely reachable, user-controlled attack paths and throw away patterns that platforms routinely reject as informative or out of scope.
These are the kinds of issues that consistently matter:
Permission review
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 79/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 234,327 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Use this when the goal is practical vulnerability discovery for responsible disclosure or bounty submission, not a broad best-practices review.
Bias toward remotely reachable, user-controlled attack paths and throw away patterns that platforms routinely reject as informative or out of scope.
These are the kinds of issues that consistently matter:
| Pattern | CWE | Typical impact |
|---|---|---|
| SSRF through user-controlled URLs | CWE-918 | internal network access, cloud metadata theft |
| Auth bypass in middleware or API guards | CWE-287 | unauthorized account or data access |
| Remote deserialization or upload-to-RCE paths | CWE-502 | code execution |
| SQL injection in reachable endpoints | CWE-89 | data exfiltration, auth bypass, data destruction |
| Command injection in request handlers | CWE-78 | code execution |
| Path traversal in file-serving paths | CWE-22 | arbitrary file read or write |
| Auto-triggered XSS | CWE-79 | session theft, admin compromise |
These are usually low-signal or out of bounty scope unless the program says otherwise:
pickle.loads, torch.load, or equivalent with no remote patheval() or exec() in CLI-only toolingshell=True on fully hardcoded commandssemgrep --config=auto --severity=ERROR --severity=WARNING --json
Then manually filter:
## Description
[What the vulnerability is and why it matters]
## Vulnerable Code
[File path, line range, and a small snippet]
## Proof of Concept
[Minimal working request or script]
## Impact
[What the attacker can achieve]
## Affected Version
[Version, commit, or deployment target tested]
Before submitting:
Alternatives
event4u-app/agent-config
Use when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.
K-Dense-AI/scientific-agent-skills
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
K-Dense-AI/scientific-agent-skills
Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.
affaan-m/ECC
Use it for engineering and operations tasks; the detail page covers purpose, installation, and practical steps.