fingerprint_normalizationTier 1 · 70% confidence
audit-trail-fingerprint-normaliz-raw-error-messages-contain-timestamps-uuids-percen-c1bfbc28
agent: audit_trail
When does this happen?
IF Raw error messages contain timestamps, UUIDs, percentages, and digit sequences that fragment fingerprints across tenants, causing identical logical events to hash differently.
How others solved it
THEN Implement a normalization pipeline that substitutes volatile substrings with stable placeholders (e.g., <ts>, <uuid>, <pct>, <n>) BEFORE hashing. Order matters: replace timestamps before generics. Use a function like normalize_message() that applies regex substitutions in a specific order, then hash the normalized string with agent name.
def normalize_message(message: str) -> str:
if not message:
return ""
text = unicodedata.normalize("NFKC", str(message)).lower().strip()
text = _RE_ISO_TIMESTAMP.sub("<ts>", text)
text = _RE_UUID.sub("<uuid>", text)
text = _RE_HEX_LONG.sub("<hex>", text)
text = _RE_PERCENT.sub("<pct>", text)
text = _RE_NUMBER.sub("<n>", text)
text = _RE_PUNCT_RUN.sub(" ", text)
text = _RE_WHITESPACE.sub(" ", text).strip()
return text
def fingerprint(agent_name: str, message: str) -> str:
h = hashlib.sha256()
h.update(((agent_name or "").strip().lower()).encode("utf-8"))
h.update(b"::")
h.update(normalize_message(message).encode("utf-8"))
return h.hexdigest()Related patterns
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