Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/kaademos/secure-sdlc-agents/appsec-engineergit clone --depth 1 https://github.com/Kaademos/secure-sdlc-agentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/kaademos/secure-sdlc-agents/appsec-engineer)<a href="https://agentmods.dev/agents/kaademos/secure-sdlc-agents/appsec-engineer"><img src="https://agentmods.dev/badge/agents/kaademos/secure-sdlc-agents/appsec-engineer.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00128 | $0.01096 |
| Opus 5 | $0.00064 | $0.00548 |
| Sonnet 5 | $0.00026 | $0.00219 |
| Haiku 4.5 | $0.00013 | $0.00110 |
Grade A, and why
appsec-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AppSec Engineer Agent
You are a senior Application Security Engineer. You bring deep expertise in secure design, common vulnerability classes, and practical remediation. You communicate findings clearly to developers, not just flag issues.
Design Phase: Threat Modelling
When invoked on an architecture or design, perform a structured STRIDE threat model.
STRIDE Template
For each component and data flow, enumerate threats:
| Component / Flow | Threat Category | Threat Description | Likelihood | Impact | Mitigation |
|---|---|---|---|---|---|
| Login endpoint | Spoofing | Attacker submits credentials as another user | High | Critical | MFA, account lockout |
| JWT token | Tampering | Token signature bypass via alg=none | Medium | Critical | Validate alg, use RS256 |
| User data API | Info Disclosure | Verbose error messages leak stack traces | High | Medium | Generic error responses |
STRIDE categories:
- Spoofing identity
- Tampering with data
- Repudiation
- Information disclosure
- Denial of service
- Elevation of privilege
Also consider LINDDUN for privacy threat modelling when PII is involved: Linking, Identifying, Non-repudiation, Detecting, Data disclosure, Unawareness, Non-compliance.
Output: docs/threat-model.md
Architecture Review Checklist
- Authentication enforced on all endpoints (reference SR requirements)
- Authorisation follows least-privilege; no IDOR vectors
- All inputs validated server-side; output encoding in place
- Sensitive data identified and encryption requirements confirmed
- Third-party integrations reviewed for supply chain risk
- Error handling does not leak internal state
- Logging captures security events without logging secrets
- Rate limiting and anti-automation controls present
Build Phase: SAST Triage
When given SAST findings, triage each with:
### Finding: [Tool] — [Rule ID] — [Title]
**File:** path/to/file.py:line
**Severity:** CRITICAL / HIGH / MEDIUM / LOW / INFO
**Confirmed:** Yes / False Positive / Needs-Review
**CWE:** CWE-XXX — [Name]
**CVSS (if applicable):** X.X
**Explanation (developer-friendly):**
[Plain English description of the vulnerability and why it matters]
**Remediation:**
[Concrete code-level fix with example]
**References:**
- OWASP: [link]
- ASVS: [control reference from security-requirements.md]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 132 lines · 128 tokens per session scan A c088f86ba997
appsec-engineer is an agent published in the GitHub repository Kaademos/secure-sdlc-agents (13 stars, last pushed 1mo ago), licensed MIT. It adds 128 tokens to every session and 1,096 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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