bug-bounty273
google223
facebook189
microsoft177
apple129
exploit103
rce96
xss88
csrf53
writeup51
defi48
smart-contract47
ethereum44
open-source44
access-control44
account-takeover40
sqli39
bragging-post38
ssrf37
aws37
docker36
ai-agents36
web335
malware35
smart-contract-vulnerability33
react32
dos31
cve31
cloudflare30
idor28
subdomain-takeover28
privilege-escalation27
wordpress26
supply-chain26
browser26
authentication-bypass25
solidity25
oauth23
node22
cors22
race-condition21
auth-bypass21
denial-of-service21
cloud21
automation20
api-security19
tool19
vulnerability-disclosure19
machine-learning18
clickjacking18
0
7/10
A technical walkthrough of building a silent data loss detection system using BigQuery's native Storage Write API metadata and built-in ML anomaly detection (AI.DETECT_ANOMALIES), implemented as a dbt incremental model that monitors hundreds of tables without external infrastructure or custom ML training.
data-quality
anomaly-detection
bigquery
storage-write-api
ml-detection
timeseries-analysis
dbt
monitoring
pipeline-validation
data-loss-detection
BigQuery
Storage Write API
WRITE_API_TIMELINE_BY_PROJECT
AI.DETECT_ANOMALIES
TimesFM
Nordnet
Pub/Sub
dbt