redteam-mindset

name	redteam-mindset
description	Red-team operator discipline — the mindset corrections that separate offensive testing from defensive WAPT. Built from authorized red-team work where conservative defaults caused multiple findings to be missed and one to be incorrectly retracted. Use at the START of any red-team engagement and again whenever feeling stuck or considering "stopping" on a defended target. The single most important skill to load when scope is "external red team" not "bug bounty / WAPT".
sources	authorized-engagement
report_count	1

When to use this skill

Trigger when:

• Engagement scope says "red team", "adversary emulation", "assume breach", "TIBER-style"
• You're tempted to retract a finding because reproducibility failed once
• You're tempted to call a defense "working as intended" instead of probing further
• You hit a blocker (captcha, rate limit, WAF, CA-block, lockout) and consider stopping
• You're about to spend time on IDOR/CSRF/XSS instead of access-yielding bugs
• You found a vuln on app A and there are sister apps B, C, D you haven't touched

DO NOT use for:

• Bug bounty programs (use bug-bounty skill — different scope rules)
• WAPT/PCI-style assessments (use OWASP-aligned skills)
• Pure compliance audits

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The one-line summary

Red team scope = "gain access, prove impact". Bug bounty / WAPT scope = "find a bug, write a report".

These produce DIFFERENT decisions at every blocker. Internalize the difference before starting.

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DO NOT STOP — primary directive (read this twice)

The 9 corrections below are nuance. THIS is the core. If you only retain one thing from this skill, retain this.

Authorization given at engagement start covers the entire engagement.

Do not insert mid-engagement permission gates. If the user chose a mode at the start ("full engagement", "Option D", "go deep", "test these assets") that authorization stands until the engagement window expires or the user explicitly revokes it. AskUserQuestion mid-loop after the user already chose a path is a stall, not a check.

Discipline rules are about correctness of FINDINGS, not throttling of EFFORT.

Read this twice. The bundle's discipline rules — OOB-Or-It-Didn't-Happen, Marker Discipline, Body-Diff, Pre-Severity Gate, Server-Policy-vs-State, Statistical Sampling — all answer one question: "is this signal actually a finding?". None of them answer the question "should I send the next probe?" The answer to that second question is always yes, unless scope is exhausted or the user said stop.

"Stop at PoC" means stop ESCALATING, not stop TESTING.

When you confirm impact on bug class X, don't keep escalating class X (no need to pivot from id=1 IDOR to dumping the whole user table). But classes Y and Z have not been tested yet. Run Y. Then Z. Then the rest of the Pattern Library.

Marker Discipline ≠ "one probe per surface."

Marker Discipline is about WHICH payloads to use (synthetic, identifiable, recoverable) — never about HOW MANY. A hardened target needs MORE marker-discipline probes than a soft one, not fewer. If the bundle's hunt-sqli Pattern Library lists 12 SQLi classes, you run 12 marker-discipline probes per parameter, not 1.

Self-throttling anti-patterns — flag immediately if you catch yourself doing any of these

These all came out of a real engagement (authorized-engagement revalidation, 2026-05-17) where this skill existed and was loaded and the operator still self-throttled. The lesson is to make the failure modes explicit:

1. Asking "want me to continue?" mid-run after the user already chose Option D / full engagement / "go deep". The answer they gave at start IS the answer.
2. Stopping at first-class-returning-401/403. The bundle has ≥12 auth-bypass classes (header tricks, method tampering, parameter pollution, JSON parser confusion, race on session create, mass-assignment on optional fields, X-Forwarded-Host SSRF in SAML callback, alg=none JWT, audience confusion, scope claim manipulation, refresh-token replay, device-code flow). Run them all per surface.
3. "Interesting constant token, not chased." If you see a token, hash, ID, or fingerprint that's constant across what should be varying responses, that's a lead, not an artifact. GET it. Decode it. Pass it back. A view.php?view=<constant-md5> redirect is a session/auth/error-key signal, not noise.
4. Reading robots.txt for cross-template signals and NOT READING the Disallow lines. A 469-line robots.txt is a developer-curated map of every path they don't want public. Every Disallow line is a probe target.
5. Treating soft-404 as "noted." A 37 KB body inside a 404 status is leaking the home page or worse. Read it. Grep it. Diff it against the home page.
6. "OpenAPI exposed → finding logged" with only 4 of N endpoints probed. Every endpoint × every relevant test class. The OpenAPI spec is the attack-surface map handed to you; not running it is throwing away a free recon.
7. "APK retest deferred — needs tooling." brew install jadx, apkpure direct download, apk-redteam-pipeline already documents the flow. Five minutes of setup, not "another session."
8. Volume framed as a problem. For an authorized engagement, 3,000 well-tagged requests through Burp is normal cadence. Bug-bounty hunters at full pace exceed that per hour. The question to ask is "have I run every test class on every live surface," not "have I sent too many requests."
9. Inserting AskUserQuestion at any decision point inside an active engagement loop. If the user picked a mode at start, that mode is in effect until revoked. Choosing operationally between e.g. SAML acs raw POST vs SAML acs replay is a technical decision the operator can make and document — it does not require user pre-approval.
10. Skill-gap-as-stop-condition. "No hunt-zoho skill exists, so I logged a v1.1 gap and moved on." NO. If a hunt-* skill doesn't exist for a discovered tech stack, do the same work using the vendor's public check matrix. Log the gap in v1.1 roadmap run the checks now.

Real-engagement cadence — what a complete sweep per live host actually looks like

Per live host, before declaring the host complete:

• Top-100 path probe (admin, api, login, /.git, /.env, server-status, swagger, openapi.json, /docs, /actuator, /healthz, /metrics, /debug, /trace, /env, /heapdump, /threaddump, robots.txt, sitemap.xml, /.well-known/*, common-CMS-paths per fingerprint)
• robots.txt content read — every Disallow becomes a probe target
• sitemap.xml content read — every entry becomes a probe target
• JS bundles harvested — grep'd with the FULL secret-regex catalogue (Firebase, AWS, GCP, JWT, Stripe, GitHub, generic high-entropy strings), route extraction, API-endpoint extraction
• Source-map variant paths checked (/*.js.map, /static/js/*.js.map, /_next/static/*.js.map, /build/*.js.map)
• For every form discovered: full SQLi marker-discipline sweep (12+ classes), auth-bypass class sweep (12+ classes), CSRF, parameter pollution, mass-assignment, race condition on state-changing submission
• For every API endpoint discovered (from JS, OpenAPI, swagger, network capture): HTTP method tampering, content-type tampering, JWT alg=none, alg=HS256-with-RS256-key, audience confusion, prototype pollution, race conditions on idempotency-violating ops
• For every SaaS tenant identified: vendor-specific check matrix from the vendor's known-vuln catalogue — even when no dedicated hunt-* skill exists yet
• Identity fabric: GetUserRealm, OpenID well-known, autodiscover-v2, federation behavior testing, sister-brand-TLD pivot for shared tenant, OneDrive-based user enum (no lockout risk)
• Mobile apps: pull every APK in the developer's catalogue, jadx decompile, secret + endpoint + cert-pin grep, exported-component enum

If you've done less than this per host, you have not finished the host. The engagement is not done until every host is finished.

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Mindset correction #1 — The blocker is data, not the stop sign

Anti-pattern (what I did wrong):

"Recheck under load showed no timing differential — recanting the SQLi as indeterminate."

The correct frame:

"The original 3-sample baseline (σ = 32 ms) with three distinct SLEEP payloads each adding +6 s is statistically definitive. The recheck failure is data — investigate the delta, not retract the finding."

When a defense suddenly appears mid-engagement:

1. Original PoC artifacts are forever — capture them BEFORE recheck. Screenshots, request/response pairs, timing samples.
2. Diff the response — body size, headers, cookies, response time. The change tells you what the client deployed (WAF rule? Hotfix? Geo block?).
3. The deployed mitigation is itself a finding — positive operational observation about IR responsiveness.
4. Try alternative vectors — slower-paced timing, encoded keywords, different injection contexts, cookie injection, header injection.
5. Document both states — "vulnerable at T0, mitigated at T0+30min, mitigation likely at WAF (bypassable)".

Rule: never retract a finding on first reproducibility failure. Investigate why before declaring false positive.

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Mindset correction #2 — Sister-app pattern recognition

Anti-pattern:

"I confirmed SQLi on /app-a/. Moving on to other tasks."

The correct frame:

"Same backend, same code template likely → /app-b/, /app-c/, /app-d/, /app-e/ (sibling apps on the same employee-portal host) are all probable. Test them with the SAME payload."

When you confirm a vuln on app A:

1. Identify shared infrastructure — same IP, same load balancer, same TLS cert, same response headers, same session cookie name, same login form HTML.
2. Identify shared code template — same form fields, same error messages, same view structure, same framework version.
3. Sweep all sisters with the SAME exploit payload immediately.
4. Document the class of vulnerability — "vulnerability is in shared form-handler template across N apps", not just one finding.
5. Recommend class-fix — fix the shared template, not just one app.

The authorized-engagement case: SQLi confirmed on one sub-app (<app-A>); four sibling sub-apps (<app-B>, <app-C>, <app-D>, <app-E>) sit on the same employee-app host with similar form patterns — likely all share the same vulnerable template. Should have been a multi-app finding.

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Mindset correction #3 — WAPT vs Red Team scope discipline

Skip these in red team scope (they don't yield access):

• IDOR (cross-user read/write without an ATO / privilege-escalation / sensitive-data-exfil chain — WAPT class). NOTE: IDOR is NOT a blanket-skip. IDOR on admin/role-assignment endpoints yields privilege escalation; on password-reset or session objects yields ATO; on file-download or PII handlers yields exfil; on token/key endpoints yields credential capture. Pursue those per the decision rule below.
• CSRF (state-change-via-tricked-user — WAPT class)
• Reflected XSS (without account-takeover chain — WAPT class)
• Missing security headers (WAPT class)
• Cookie hardening flags (WAPT class)
• Verbose error messages without sensitive data (WAPT class)
• DoS (out of scope per engagement rules typically)
• Username enumeration (intel-gathering, not access)

Pursue these (they DO yield access):

• SQL injection (data exfil → DB creds → lateral)
• Command injection / RCE (foothold)
• File upload → webshell (foothold)
• LFI/RFI (config reads → DB creds → access)
• SSRF (cloud metadata → IAM → cloud access)
• Authentication bypass (parameter manipulation, JWT alg=none, header injection)
• Hardcoded credentials in mobile/JS bundles
• Default credentials on admin panels
• SAML XSW / signature stripping (session hijack)
• Cisco ASA / Citrix / Pulse / Fortinet SSL VPN CVEs (network foothold)
• ManageEngine / Confluence / Atlassian RCE CVEs (foothold)
• Kerberoasting / AS-REP roasting (post-foothold, but enumerate from outside if possible)

Decision rule: if the bug, exploited fully, doesn't lead to a session/token/foothold or sensitive data exfil, it's WAPT-class — note it briefly but don't burn time on it.

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Mindset correction #4 — Aggressive default, not conservative default

Anti-pattern:

"Tested 30% of the websites and called it comprehensive."

The correct frame:

"Until I've actively probed every login form, every API endpoint, every parameter, every CVE-matched version, the engagement is not done."

Aggressive defaults:

1. Probe every live host for top 20 paths (admin, api, login, /.git, /.env, server-status, swagger, openapi.json, robots.txt, /actuator, /healthz, etc.)
2. For every login form discovered, attempt 1-of-leaked + 1-of-spray-pattern + SQLi + auth-bypass-via-parameter-tampering
3. For every JS bundle, grep for hardcoded API keys, JWT, base URLs, hidden endpoints, admin paths
4. For every API endpoint, check OPTIONS preflight, missing-auth response, alg=none JWT, X-Forwarded-User header injection
5. For every mobile app, decompile + grep for secrets + check pinned certs + identify exported components
6. For every "out of scope" SaaS that's on a corp subdomain, confirm with client — vendor-managed doesn't mean immune (CVE-2022-47966 went unpatched on many on-prem ME-SDP installs)

Rule: if you haven't actively probed every live surface (not just a sampled fraction), you haven't done red team yet — you've done recon.

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Mindset correction #5 — Persistence beats elegance

Anti-pattern:

"Tesseract failed on 3 captchas, gave up, declared captcha bypass not feasible."

The correct frame:

"Tesseract failed. Decision tree: try preprocessing (binarize, denoise, upscale, multi-PSM), then trained-model OCR, then paid solving service ($5/mo for engagement-grade volume), then session-bound captcha replay attack. A real attacker WILL invest the $5."

Decision-tree for blockers:

Captcha:

1. Omit field → check if required
2. Empty value → check validation
3. Reuse value across multiple submits → check session-bind
4. Tesseract with preprocessing
5. Trained-model OCR (deep-text-recognition-benchmark, calamari-OCR)
6. Paid solving service (2captcha API, anti-captcha)
7. Audio captcha if available (much weaker)

WAF:

1. Slower pace
2. Encode the payload (URL, hex, base64, mixed case)
3. Different injection context (cookie, header, JSON)
4. Different HTTP verb
5. Different content-type (multipart, application/json)
6. Bypass at the host level (X-Forwarded-Host, X-Original-URL)
7. Probe origin server directly (find via certificate transparency)

Rate limit:

1. IP rotation (multiple cloud regions)
2. User-Agent rotation
3. Slower pace + jitter
4. Distribute across multiple TLS sessions

Slow target (timing-based exfil too slow):

1. Different injection point (avoid per-row SLEEP context)
2. BENCHMARK or GET_LOCK as alternate timing oracle
3. Error-based extraction
4. OOB DNS callback (interactsh)
5. Faster network (cloud VM in same region as target)
6. Run dumper unattended overnight; deliver partial results

Rule: when one path fails, the next move is "another vector to the same goal", not "documented as not vulnerable". A real adversary doesn't have an engagement window.

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Mindset correction #6 — Real-time IR observation is a finding

When the client SOC patches mid-engagement (you observe a vulnerability disappear during your test):

• Treat it as evidence, not as a failure
• Capture timestamps before and after the change
• Document as positive operational finding — "client SOC detected and mitigated within X minutes; mitigation deployed at WAF/code level"
• Verify the mitigation depth — WAF rule (bypassable) vs code fix (real)
• The original PoC remains the vulnerability finding — patching doesn't erase it

This is its own skill: see mid-engagement-ir-detection.

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Mindset correction #7 — Multi-technique cross-validation

For every "vulnerable" finding, prove via 2+ techniques:

Vuln class	Primary	Cross-check
Time-based blind SQLi	SLEEP() differential	Different SLEEP variants (3 distinct payloads min)
Boolean blind SQLi	Body-size differential	Different boolean comparisons
Error-based SQLi	Error message reflection	UPDATEXML + EXTRACTVALUE both
RCE	Command output reflection	OOB callback (interactsh DNS)
LFI	File content reflection	Different file paths, different encodings
SSRF	Internal-only response	OOB callback (interactsh DNS)
Valid credential (M365)	ROPC + AADSTS53003	SAML SSO browser flow + ConvergedConditionalAccess page
Auth bypass	Logged-in landing page	Session cookie persistence on subsequent request

A single signal can be coincidence (network jitter, server hiccup, cache). Two distinct signals from the same root cause is definitive.

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Mindset correction #8 — Engagement journal discipline

Real-time, append-only, structured:

{"ts":"2026-05-08T14:40:53","ip":"<src-ip>","tool":"m365_validator","target":"login.microsoftonline.com","payload":"user1@<client>.example:<pw-r4>***","resp_code":400,"resp_body_size":154,"resp_ms":1280,"aadsts":"AADSTS53003","verdict":"VALID_CA_BLOCK","notes":""}

Why:

• Forensic record of what was tested and when
• Surfaces patterns (clustering, timing changes, error code distribution)
• Becomes evidence for the report
• Survives into next engagement as priors
• Differential analysis: "What changed between window A and window B?"

Anti-pattern: ad-hoc shell commands with no logging. You will lose the original PoC timestamp when you need it most (recheck failed, can't prove the original signal was real).

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Mindset correction #9 — Time is the constraint, not skill

A real adversary has months. You have an engagement window (weeks). Decisions:

• Don't pre-judge feasibility — if a dumper would take 6 hours, run it overnight; deliver partial results in the morning.
• Parallelize. Run multi-target tests concurrently. Burn CPU, not wall-clock.
• State persistence. Engagements span multiple sessions. State files (engagement_log/) make Wednesday's work usable on Friday.
• Background long-running jobs — kick them off, set monitors for events, do other work in parallel.
• Don't repeat yourself — if you tested target X with payload Y on Tuesday, Wednesday you should know that without re-testing.

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Pre-engagement checklist

Before starting a red team engagement, confirm:

• Scope clear (subdomains in/out, SaaS in/out, phishing in/out, implant in/out)
• SOW + EL/RoE referenced
• Test IPs allocated and logged (IP_LOGS table or equivalent)
• State file initialized (engagement_log/ with attempt counter, results JSONL, IP log)
• Hard-cap for cred attacks decided (1 or 2 per user lifetime)
• Kill-switch thresholds set (max LOCKED in run, max errors in window)
• Crown-jewel target identified (what does winning look like?)
• Critical-finding-discuss protocol agreed (when to pause and notify)
• Burp proxy as default for evidence capture
• Engagement journal initialized

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During-engagement checklist

Every 30 minutes ask:

• Am I making progress, or stuck?
• Have I logged the last test result to the engagement journal?
• Is the IP I'm testing from logged?
• If I confirmed a vuln: have I tested sister apps with same backend?
• If I hit a blocker: did I try the next vector in the decision tree?
• If I'm tempted to "stop" — am I sure scope is exhausted, or am I just tired?

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Post-engagement checklist

Before declaring done:

• All findings have at least 2 cross-technique confirmations
• Each finding's PoC is reproducible in <5 minutes by another tester
• Original PoC artifacts (screenshots, request/response, timing samples) preserved
• Mid-engagement IR observations documented as findings (positive ops)
• Active-attacker observations documented (lockout differentials, etc.)
• Sister-app sweep complete for every shared-infra finding
• State files preserved for future engagement
• Tooling gaps logged (what would have changed outcomes)

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Anti-patterns to flag immediately

If you catch yourself thinking any of these, STOP and reconsider:

• "It's not vulnerable" (have I tested 3 vectors? have I tested sister apps?)
• "The defense is working" (have I tried alternative payloads? slower pace? different protocol?)
• "Recheck failed so it must have been a false positive" (NO — investigate the delta)
• "OCR isn't reliable, can't bypass captcha" (paid service is $5; we're not on a personal-research budget)
• "Mobile app is years old, probably nothing useful" (hardcoded URLs and tokens often outlive the engineering team's memory)
• "SaaS, so nothing to test" (vendor patches centrally — usually true, but tenant config gaps are NOT central)
• "We've tested enough" (use the during-engagement checklist; if any answer is "no", keep going)
• "The exfil would take too long" (run it unattended; deliver partials)

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When to stop (the legitimate stop conditions)

Only stop when:

• All in-scope assets have been actively probed (not just discovered) for top vuln classes — see "Real-engagement cadence" checklist near top of this skill
• Every confirmed vuln has been validated via 2+ techniques
• Every confirmed vuln has been swept on its sister apps
• Every blocker has been attempted via 2+ alternative vectors
• Engagement window has expired AND deliverables are documented
• Client has explicitly directed you to stop

NOT legitimate stop conditions (each of these has produced a real failure):

• "I'm tired of this target"
• "The first attempt didn't work"
• "Defenses are working" — defences working on class X says nothing about classes Y, Z
• "I documented it" — documenting a gap is not running the test
• "We've already informed the client"
• "Volume is getting high" — for an authorized engagement, the only volume question is whether each request is well-tagged and audited
• "The discipline rules say be careful" — they say be correct, not be quiet
• "The skill for this tech stack doesn't exist yet" — apply the vendor's public check matrix manually; log v1.1 gap separately
• "User chose Option X and I'm not sure if X covers Y" — if X was a full-engagement mode, Y is in scope unless the user said otherwise
• "Tool isn't installed" — brew install, apt install, direct-download → most engagement tools install in under 5 minutes
• "I'll defer to operator" — the operator authorized you to do the work. Doing the work IS the deferral they want.

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Bridge to neighboring skills

After internalizing this mindset, layer the technique-specific skills:

• m365-entra-attack — M365 credential attack chain
• mid-engagement-ir-detection — turning client SOC patches into findings
• hunt-sqli — SQL injection across techniques
• hunt-rce — RCE across vectors
• bug-bounty — for distinguishing red-team vs bb scope when working dual-track

This skill is the operational discipline; those are the techniques.

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Related Skills & Chains

• hunt-dispatch — Once mindset is loaded, the /hunt command needs a mode answer (redteam vs wapt, blackbox vs greybox) before it routes to platform-specific skills. Engagement flow: red-team mindset triggered → confirm engagement mode (bug-bounty vs red-team vs pentest per project memory) → invoke /hunt → hunt-dispatch loads the right cluster (M365 / SharePoint / VPN / vCenter / APK).
• mid-engagement-ir-detection — Red-team mindset says "behavior changes ARE findings"; this skill operationalizes that. Engagement flow: red-team engagement underway → baseline established at session start → response patterns shift mid-test → mid-engagement-ir-detection captures the SOC-patch state as a NEW finding (defensive-action observed = client capability metric). Don't dismiss it as "the bug got fixed."
• redteam-report-template — Red-team deliverable is NOT a bug-bounty report; different audience, different tone, different cadence. Engagement flow: findings collected throughout engagement → at session close, package via redteam-report-template (Subject / Observations / Description / Impact / Recommendation / PoC) for client-facing DOCX, not report-writing which is for H1/Bugcrowd/Intigriti platforms.
• triage-validation — Red-team mindset includes "don't retract too fast" — the 4 retractions from an authorized engagement were mindset failures, not validation failures. Engagement flow: every finding through triage-validation 7-Question Gate, but with the red-team adjustment that "exploitable only with chain" is still a finding, not a no-finding.
• evidence-hygiene — Red-team engagements often span weeks; without disciplined evidence capture the deliverable suffers. Engagement flow: red-team mindset triggered → set up evidence-hygiene capture cadence (screenshots, request/response dumps, timestamped logs) at session start, not at session close.