CC attacking-oauth-with-device-code-phishing
Run OAuth 2.0 device-code and illicit-consent phishing attacks against Microsoft Entra ID, using TokenTactics-style tooling to steal access and refresh tokens, bypass MFA, and pivot across Microsoft 365 services. Use for authorized red-team engagements simulating device-code or consent-grant phishing against a tenant you have explicit written permission to test.
Run OAuth 2.0 device-code and illicit-consent phishing attacks against Microsoft Entra ID, using TokenTactics-style tooling to steal access and refresh…
As a process C 55/100 · Has gaps — weak spots: result and completion, failures and branches, running it twice
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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:200High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)4. The consented OAuth grant persists as a service-principal grant in the victim tenant until an admin revokes it (`Remo…ant`).
quoted -
low Risky intent
intent-offensive-securitySKILL.md:222Offensive-security / dual-use content (legitimate for authorised testing; review intended use)| Microsoft / Storm-2372 advisory | Device-code phishing campaign analysis | https://www.microsoft.com/en-us/security/blog/ |
Files scanned: 5. 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 55/100
- 0Result and completion. Does not say what the result is
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 4 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 45 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3611 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -42 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
- +3Description length 364: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 45 items
- +4Has examples (12 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.