Regex Dos with Hmac Signatures

Regular expression denial of service (ReDoS) in HMAC signature verification occurs when attackers craft inputs that cause catastrophic backtracking in the regular expressions used to parse or validate signature components. This creates a perfect storm: HMAC signatures are designed to be tamper-proof, but their validation logic can become the attack vector itself.

The most common manifestation appears in timestamp parsing. Consider a signature header like:

Authorization: HMAC-SHA256 Credential=AKIAIOSFODNN7EXAMPLE/20231201/us-east-1/s3/aws4_request, SignedHeaders=host;x-amz-date, Signature=5d672d79c15b13162d9279b0855cfba6789fa39926f9c514ffd5...

Attackers can exploit timestamp validation with crafted inputs like:

(?:(?:x+)+)+

This pattern causes exponential backtracking when matching against time strings. A 20-character malicious timestamp can take seconds to validate, while legitimate timestamps process in microseconds. The worst-case scenario: a single API endpoint handling 100 requests/second with a 2-second ReDoS vulnerability becomes a 200x capacity amplification attack.

Another critical vector is header extraction using regex patterns. Many implementations use patterns like:

const signedHeaders = /SignedHeaders=([^,]+)/.exec(header)

Malicious inputs can include nested alternations or repeated groups that trigger catastrophic backtracking. The HMAC verification process typically involves multiple regex operations—parsing the header, extracting signed headers, validating timestamps—each creating potential amplification points.

The authentication context makes this particularly dangerous. HMAC verification often occurs early in request processing, before rate limiting or authentication checks. This means attackers can bypass standard protections by exploiting the very mechanism meant to secure the API.

Detecting ReDoS in HMAC implementations requires understanding both the cryptographic validation flow and regex attack patterns. The key insight: HMAC signatures use predictable structures that create predictable regex vulnerabilities.

Static analysis should focus on these patterns:

const signatureRegex = /HMAC-SHA256 Credential=([^/]+)/([^,]+), SignedHeaders=([^,]+), Signature=([a-f0-9]+)/i

This pattern is vulnerable to nested quantifiers and alternation attacks. Look for:

• Repeated groups with '+' or '*' quantifiers
• Alternations inside groups: (a|b|c)
• Backreferences that create complex matching states
• Timestamp validation with flexible formats

Dynamic detection requires timing analysis. HMAC verification should complete in microseconds. Any validation taking >10ms for typical inputs indicates potential ReDoS. Use timing-based fuzzing:

function testReDos(header) {
  const startTime = performance.now()
  try {
    verifyHMAC(header, secretKey)
    return performance.now() - startTime
  } catch {
    return performance.now() - startTime
  }
}

Monitor for exponential time growth as input size increases. A safe implementation shows linear or sub-linear scaling.

middleBrick's approach combines static pattern analysis with active probing. The scanner tests HMAC endpoints with crafted inputs targeting common regex anti-patterns in signature parsing. It measures response times across input variations to identify quadratic or exponential behavior. The LLM security module also checks for prompt injection in any AI-assisted HMAC implementations, though this is less common in traditional HMAC usage.

The fundamental principle: replace regex with deterministic string operations for HMAC signature parsing. String splitting and substring operations have predictable O(n) performance regardless of input content.

For timestamp validation, use strict format checking combined with semantic validation:

function validateTimestamp(ts) {
  if (!/^//d{8}$/.test(ts)) return false
  const date = new Date(ts.slice(0,4), ts.slice(4,6)-1, ts.slice(6,8))
  return date && date.toISOString().slice(0,10).replace(/-/g, '') === ts
}

This approach validates format and semantic correctness without regex backtracking. The strict pattern ensures only valid dates pass, while the Date constructor catches invalid dates like '20231301'.

For credential extraction, use structured parsing:

function parseCredential(header) {
  const credMatch = header.match(/Credential=([^,]+)/)
  if (!credMatch) throw new Error('Missing credential')
  
  const [type, keyId, date, region, service, request] = credMatch[1].split('/')
  if (type !== 'HMAC-SHA256') throw new Error('Invalid credential type')
  
  return { keyId, date, region, service, request }
}
Notice the use of split() instead of nested regex groups. Each operation is O(n) with no backtracking possibilities. The credential format is predictable enough that structured parsing is both safer and more maintainable.
Finally, implement constant-time comparison for the actual signature verification to prevent timing attacks:
function timingSafeEqual(a, b) {
  if (a.length !== b.length) return false
  let result = 0
  for (let i = 0; i < a.length; i++) {
    result |= a.charCodeAt(i) ^ b.charCodeAt(i)
  }
  return result === 0
}
This ensures the verification process itself doesn't leak information through timing variations, complementing the regex DoS protection with timing attack resistance.