raven-devsec-mythos-class

name

raven-devsec-mythos-class

description

Mythos-class source-code reasoning for DevSec — pre-merge, pre-deploy, pre-release. Use when the user says "review this PR for security", "audit this diff", "block bad merges", "secure code review", "DevSec gate", "shift-left security", "pre-deploy security scan", "release security gate", or asks Raven to act as a Mythos-grade auditor inside the CI/CD pipeline. Every finding terminates at a tool oracle (𝒯), classical-ML detector (𝓜), or scored hypothesis (𝓛) with a falsification test — never raw LLM speculation — and ships with the D3FEND Harden technique id it implements. Defender-only: emits findings + remediation candidates, never exploit payloads.

Raven — DevSec (Mythos-class)

This skill is Raven's DevSec gate. It takes the design property that makes Mythos useful — strong source-code reasoning paired with an explicit threat model and a validation harness — and ports it into a defender-only, CI/CD-integrated, D3FEND-grounded workflow.

The skill explicitly answers the criticism XBOW made of Mythos used alone: "needs precise prompts, explicit threat models, and validation infrastructure to turn strong reasoning into reliable security outcomes" (XBOW Mythos evaluation, May 2026). Raven supplies the harness; the LLM supplies the reasoning; the tool oracles supply the grounding.

When to use

Trigger when the user asks any of:

• "Review this PR / diff / commit / branch for security"
• "Audit this codebase before release"
• "DevSec gate before merge / before deploy / before release"
• "Shift-left security review"
• "Block insecure merges automatically"
• "Mythos-class source audit on this repo"
• "Security review with threat model <file>"

Do not trigger for: post-deploy 0-day hunting (use raven-zero-day-hunter), live-system detection (use raven-zero-day-detection), or pattern library curation (use raven-zero-day-threat-patterns).

What makes this "Mythos-class"

The XBOW evaluation identified four properties of Mythos that matter for source-code audit:

1. Source-code reading > source-code writing (strong reasoning over existing code).
2. Honest about ceiling — flags issues that need runtime/configuration validation.
3. Literal-rule discipline — rejects false positives well, but can lose true positives when evidence does not formally satisfy criteria.
4. Strong in native code and reverse engineering, not just web app code.

This skill operationalizes all four — and binds (3) (the false-negative risk) to mandatory raven-zero-day-hunter escalation, so issues that fail the literal-rule test do not silently vanish.

Inputs

Required:

1. Scope — one of:
   • pr — pull request (repo + base ref + head ref)
   • diff — explicit unified diff
   • commit-range — repo + commit range
   • branch — repo + branch
   • release-candidate — repo + tag
2. Threat model — path to a THREAT_MODEL.md file OR an inline threat model block. The skill REFUSES to run without one. This is the property the XBOW post identified as essential for Mythos-class accuracy.
3. Verification depth — pre-merge (≤ 5 min, blocking), pre-deploy (≤ 30 min), pre-release (≤ 2 hours, includes fuzz + formal where applicable)

Optional:

• Approval mode — smart for advisory comments, manual for merge-blocking
• Cost cap — default scales with depth: $1 / $5 / $20
• Pattern pack version — pinned SHA from raven-zero-day-threat-patterns export

Threat model schema (mandatory)

threat_model_id: TM-2026-01
asset_class: <web-app|api|smart-contract|kernel-module|binary-service|library>
trust_boundaries:
  - name: client_to_server
    untrusted_inputs: [http_body, http_query, http_headers, websocket_frames]
  - name: server_to_db
    untrusted_outputs: [sql_query, redis_key, mongodb_filter]
critical_invariants:
  - name: no_user_can_access_other_users_resources
    enforced_by: [middleware.authz, repository.scoped_query]
  - name: all_external_io_is_logged
    enforced_by: [interceptor.audit]
adversary_capabilities:
  - submit_arbitrary_http_input: true
  - control_dns_response: false
  - read_filesystem_directly: false
in_scope_cwes:
  - CWE-89   # SQL Injection
  - CWE-862  # Missing Authorization
  - CWE-79   # XSS
     

     

   
   

The threat model is the "precise prompt" XBOW called out. Without it the skill cannot distinguish "literal rule met" from "spirit of rule met" — Mythos's documented weakness.

Pipeline — seven mandatory stages

Stage 1 — Scope resolution (𝒯-grounded)

1. Materialize the diff:
   • pr → gh pr diff via the GitHub connector (read-only)
   • commit-range → git diff <base>..<head>
   • branch → git diff origin/main..<branch>
   • release-candidate → git diff <previous-tag>..<tag>
2. Bucket changed files by language and target type. Reject if any file is in a denylist (vendored/, *.lock, generated code) — these go through a separate stricter path.
3. Compute change blast radius:
   • Lines added / removed
   • Public-API surface changed (export list diff)
   • Dependencies changed (Cargo.toml, package.json, requirements.txt diff)
   • IaC / config changed (*.tf, *.yaml, Dockerfile)

Output: ScopeManifest. The skill rejects scopes exceeding pre-merge depth's line cap (default 2,000 changed lines) — over-large changes are routed to pre-deploy or pre-release depth.

Stage 2 — Threat-model alignment (𝒯-grounded)

1. Parse the threat model with schema validation.
2. For each changed file, identify which trust_boundaries and critical_invariants it touches via AST analysis in raven/ml/code_flow_scanner.py.
3. Build a ThreatProjection: for every changed function, list which invariants apply and which adversary capabilities are relevant.

A change that does not project onto any invariant is not free-pass — it is flagged for "no-invariant coverage" and surfaced separately. This catches the Mythos failure mode where evidence does not formally satisfy criteria because the criteria were never written down.

Stage 3 — Source-code reasoning pass (𝓛-scored)

This is the Mythos-class core. The skill invokes raven/hunters/hypothesis_generator.py with three precise inputs:

• The unified diff
• The ThreatProjection from Stage 2
• The relevant pattern subset from raven-zero-day-threat-patterns (filtered by in_scope_cwes)

The LLM produces a ranked list of SecurityHypothesis records. Each MUST include:

• cwe (must be in threat model's in_scope_cwes, OR explicitly flagged as out-of-scope-but-noticed)
• location — file + line range or symbol
• precondition — what attacker input or state is required
• invariant_broken — which critical_invariant from the threat model this would violate
• prior ∈ [0, 1]
• falsification_test — concrete tool-oracle invocation that would refute the hypothesis
• evidence_quote — the exact diff lines that prompted the hypothesis (verbatim, no paraphrase)

The LLM MUST NOT propose hypotheses without an evidence_quote. This enforces XBOW's "literal evidence" discipline.

Stage 4 — Falsification pass (𝒯-grounded, mandatory)

For every hypothesis from Stage 3, run its falsification_test against a sandbox build:

Target	Validator
solana-program	raven/tools/ares.py (Solana ruleset)
evm-contract	raven/tools/ares.py (EVM ruleset)
c-cpp-source / rust-source	raven/ml/code_flow_scanner.py (taint) + raven/ml/memory_analyzer.py
python-source / js-ts-source	Semgrep via code_flow_scanner.py + raven/ml/variant_analyzer.py
kernel-module	raven/tools/ghidra_analyzer.py (post-build) + memory analyzer
binary-service	raven/tools/ghidra_analyzer.py + raven/tools/radare2.py

Outcomes per hypothesis:

• confirmed — oracle reproduces the violation against the staged build
• refuted — oracle returns evidence inconsistent with the hypothesis
• inconclusive — oracle could not run or returned mixed signal
• runtime_required — oracle cannot statically resolve; needs runtime validation (this is the honest-ceiling output Mythos is known for)

A runtime_required outcome at pre-merge depth is NOT a free pass — the hypothesis is recorded as a deferred_finding and the gate emits a comment requesting pre-deploy re-run with live-site access.

Stage 5 — Spirit-vs-letter cross-check

XBOW found Mythos prioritizes letter over spirit (77.8% vs Opus 4.6's 81.2% on command-safety benchmark). The skill explicitly counters this:

1. For every hypothesis the LLM marked refuted, take the related critical_invariant from the threat model and run a second pass with the invariant as the explicit hypothesis ("does this diff violate <invariant>?").
2. If the second pass produces a new confirmed hypothesis, emit a letter_to_spirit_recovery finding — these are flagged as high-value because they would have been false negatives under literal-only reasoning.

This is the harness that turns Mythos's discipline into a strength instead of a blind spot.

Stage 6 — D3FEND Harden binding (𝒯-grounded)

For each confirmed and letter_to_spirit_recovery finding:

1. Call raven.d3fend.api.cwe_to_d3fend(finding.cwe) and filter to tactic Harden.
2. Rank by overlap count: techniques returned by both cwe_to_d3fend AND attack_to_d3fend(known_attack_for_cwe) rank higher.
3. Attach the top 1–3 D3FEND ids to the finding.

Common bindings:

CWE	Likely D3FEND Harden
CWE-89 (SQLi)	D3-IVV (Input Value Validation), D3-SCH (Source Code Hardening)
CWE-862 (Missing Authz)	D3-AH (Application Hardening), D3-SCH
CWE-79 (XSS)	D3-IVV, D3-MOA (Message-Oriented Authentication)
CWE-918 (SSRF)	D3-NTPM (Network Traffic Policy Mapping), D3-AH
CWE-787 (OOB Write)	D3-SCH, D3-PSEP (Process Segment Execution Prevention)
CWE-119 (Memory Bounds)	D3-SCH, D3-MBT (Memory Boundary Tracking)

Bindings are derived from the ontology, never hardcoded in the skill — the table above is illustrative.

Stage 7 — Remediation candidate generation (𝓛-scored, 𝒯-bound)

For each confirmed finding, generate up to 3 patch candidates via raven/mitigation/remediation_engine.py:

• Each candidate MUST pass regex / shlex safety checks the engine already enforces
• Each candidate MUST pass the threat model's invariant assertions on a re-staged build
• The skill DOES NOT apply patches in this skill — application is handed off to raven-zero-day-fixing

Output is RemediationCandidate records attached to each finding, so the PR comment can include Apply suggestion links.

CDP contract — quick check before returning

assert every finding.evidence_quote is verbatim from the diff
assert every confirmed finding has at least one tool-oracle hit (𝒯)
assert every finding.d3fend_techniques resolves through raven.d3fend.api
assert findings without runtime validation are marked deferred, not confirmed
assert no out_of_scope_cwes findings are gating (advisory only)

Gate decision matrix

Verification depth	Confirmed in-scope findings	Letter-to-spirit findings	Deferred runtime-required	Decision
pre-merge	≥ 1 critical	any	any	BLOCK
pre-merge	≥ 1 high	any	any	REQUEST_CHANGES
pre-merge	medium / low only	none	any	COMMENT
pre-merge	none	none	none	APPROVE
pre-merge	none	none	≥ 1	APPROVE_WITH_DEFERRED_NOTE
pre-deploy	≥ 1 critical / high	any	any	BLOCK
pre-deploy	medium only	any	≥ 1 still deferred	REQUEST_CHANGES
pre-release	any unresolved confirmed	any	any	BLOCK

Critical / high / medium / low severities are computed from (prior × oracle_confidence × invariant_criticality) per the threat model — not from CVSS lookups.

Output contract — PR comment / report

# Raven DevSec Review — <pr/diff/branch ref>

## Verdict: <APPROVE|APPROVE_WITH_DEFERRED_NOTE|COMMENT|REQUEST_CHANGES|BLOCK>

## Scope
- Files: <n> / Lines: +<a> -<r>
- Public API changed: <yes|no>
- Dependencies changed: <list>
- Threat model: <id> (`<path>`)

## Findings (<count>)

### F-<n> — <one-line summary>
- Severity: <critical|high|medium|low>
- CWE: <id>
- Invariant violated: <name from threat model>
- Location: <file:line-range>
- Evidence quote:

``` - Falsification test: - Oracle outcome: - D3FEND Harden: - Remediation candidates: - C1: (``) - C2: (``) - Suggested apply skill: `raven-zero-day-fixing`

(repeat per finding)

Letter-to-spirit recoveries ()

Finding	Invariant	Why initial pass missed it
...

Deferred runtime-required ()

Hypothesis	Why deferred	Required next step
...	needs live request	re-run at pre-deploy depth

Out-of-scope notices ()

Finding	Why advisory only	Out-of-scope CWE

No-invariant-coverage warnings ()

Change	File	Why concerning

Reproducibility kit

• Threat model SHA:
• Pattern pack SHA:
• Tool versions:
• Oracle traces:
• Commit:

## CI / CD integration

The skill is designed to run as a GitHub Action / GitLab CI job. Hooks:

- `pre-merge` — GitHub PR check, blocks merge on `BLOCK` and `REQUEST_CHANGES`
- `pre-deploy` — runs after merge to main, blocks deployment pipeline
- `pre-release` — runs against release-candidate tags before public release

The skill MUST post results back as PR review comments with a stable bot identity, and MUST attach the full report as a workflow artifact for audit.

For GitHub specifically, use the connected `github_mcp_direct` integration:

- Read: `gh pr view`, `gh pr diff`
- Write: PR review with one of `APPROVE`, `REQUEST_CHANGES`, `COMMENT`
- The skill MUST NOT push commits, force-push, or close PRs.

## DevSec workflow recipes

### Recipe A — Block-on-merge for high-severity-only repos

```yaml
on: pull_request
jobs:
  raven_devsec:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with: { fetch-depth: 0 }
      - run: raven devsec review
        env:
          RAVEN_DEPTH: pre-merge
          RAVEN_THREAT_MODEL: .raven/THREAT_MODEL.yaml
          RAVEN_APPROVAL: smart

Recipe B — Two-stage gate (advisory at PR, blocking at deploy)

PR job runs pre-merge in advisory mode (smart). Deploy job runs pre-deploy in blocking mode (manual for any high+). This matches the Mythos "honest ceiling" philosophy: low-cost reading at PR time, deeper validation when the change is about to face the runtime.

Recipe C — Release-gate with formal verification (Solana / EVM)

For smart contracts. pre-release depth invokes the formal-verification stub in raven/ml/vulnerability_validator.py. Findings that cannot be formally discharged block the release-tag pipeline.

Refusal rules

1. Refuse to run without a threat model. No default threat model exists. The skill suggests raven devsec init to bootstrap one.
2. Refuse to gate on findings derived from LLM speculation only — every finding must have evidence_quote from the diff AND oracle confirmation (or be marked deferred_runtime_required).
3. Refuse to apply patches. Application is raven-zero-day-fixing's job.
4. Refuse to bypass the approval gate when posting BLOCK or REQUEST_CHANGES.
5. Refuse to mark a hypothesis refuted without also running the spirit-pass in Stage 5.
6. Refuse to operate on repos the user has not authorized via the GitHub connector.
7. Refuse to import any defender-edition-excluded module (offensive.py, metasploit_integration.py, empire_client.py, exploitdb*.py).

Mythos parity & honest divergence

Mythos property (per XBOW)	This skill	Divergence rationale
Strong source-code reading	Yes — Stage 3 LLM reasoning with diff + threat model	None
Strong native-code / RE	Yes — Stage 4 routes to Ghidra / radare2	None
Honest about runtime ceiling	Yes — deferred_runtime_required is a first-class outcome	None
Literal-rule precision	Yes — evidence_quote mandatory	None
Letter-over-spirit weakness	Mitigated by Stage 5 spirit-pass against invariants	Defender cannot afford silent false negatives
5x cost of Opus	This skill is model-agnostic; default routes to cheaper models with pre-merge and only escalates to higher-tier on pre-release	DevSec runs at PR cadence — cost must scale with depth
Offensive-oriented (XBOW use case)	Defender-only; emits findings + remediation, never exploit payloads	OpenAI Cybersecurity Grant scope

Related skills

• raven-zero-day-threat-patterns — supplies the pattern subset for Stage 3 prompt context.
• raven-zero-day-hunter — invoked when a finding requires deep deferred analysis beyond pre-release depth.
• raven-zero-day-investigator — invoked when a runtime confirmation arrives post-deploy.
• raven-zero-day-defend — invoked when a confirmed finding maps to in-the-wild active campaigns.
• raven-zero-day-fixing — sibling skill that applies the remediation candidates this skill generates.
• D3FEND OWL integration (raven/d3fend/) — source of every Harden technique id (D3FEND home, MITRE 1.0 release announcement).

Provenance & honest comparison

The design of this skill is informed by three public sources:

• XBOW Mythos evaluation, May 2026 — for Mythos's documented strengths and the specific failure modes (letter-vs-spirit, runtime ceiling) that this skill mitigates by design.
• CISA / NSA principles for security-by-design and -by-default — for the shift-left framing and the requirement that security be a pipeline property, not a post-hoc audit.
• Anthropic AI for Cyber Defenders — for the Cybergym-style trial/cost budget pattern reused in the verification-depth ladder.

The skill is positioned as the defender-only, D3FEND-grounded complement to the offensive Mythos+XBOW pairing: same source-code reasoning class, opposite goal.