Security teams should first collect the blob contents into a local, inspectable location, then run a dedicated secret scanner across the downloaded files. The scanner should verify suspected secrets against provider APIs where possible, because verification sharply reduces false positives. Archive handling matters too, since compressed files can hide valid credentials inside nested content and backups.
Why the download-and-scan pattern matters for Blob Storage
Blob Storage is easy to miss if teams only scan repositories or ticket attachments. The practical problem is not just that a secret may appear in a plain file, but that it may be wrapped inside a compressed archive, nested bundle, export, or backup artifact. A scan that only inspects top-level objects will undercount exposure and give false confidence.
That is why the first step is to materialise the blob contents in an inspectable workspace before scanning. Once files are unpacked and normalised, a secret scanner can evaluate the actual content rather than the container format. This approach is especially important when teams are trying to find leaked API keys, tokens, certificates, or service credentials that were archived for convenience rather than for protection.
One useful reference point is the problem of secrets sprawl described in Guide to the Secret Sprawl Challenge, where credentials are often embedded in ordinary operational artefacts rather than stored where defenders expect them.
How to avoid missing embedded files, archives, and false positives
The scan workflow should be recursive. That means extracting archive layers, enumerating nested files, and scanning the expanded contents, not just the original blob object. Teams should also preserve file context, because archive members, paths, and surrounding metadata often help distinguish a real secret from a harmless string that merely resembles one.
Verification is the second control that changes the quality of results. A secret scanner should validate suspected secrets against provider APIs when feasible, because pattern matching alone tends to over-report and bury the useful findings. Verification is most valuable for cloud keys, tokens, and other credentials that expose an active account or service if they are still valid.
For teams building a broader hunt process, Ultimate Guide to NHIs, Static vs Dynamic Secrets is a good companion because it explains why long-lived secrets are especially risky once they are discovered in stored content.
Risk and Threat Considerations
Blob Storage becomes a high-value search target when archives, exports, or backups preserve secrets that other controls no longer track. The risk is not only accidental disclosure, it is also delayed discovery, because one overlooked nested file can keep a live credential available long after the original system has changed.
Failure mechanism: Scanners that do not recurse into archives, compressed bundles, or nested attachments miss secrets that are present only inside child files, while scanners that do not verify findings generate noisy output that can hide the real exposures.
Impact: Missed credentials can remain usable for lateral access, cloud abuse, or service impersonation, and repeated false positives can degrade trust in the scanning program until teams stop acting on it.
The threat pattern aligns with documented secrets leakage and credential exposure cases, including the 230M AWS environment compromise, where exposed configuration material created direct access risk.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 address the attack and risk surface, while CIS Controls v8 and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-03 — Secrets and Credential Management | Blob scans seek exposed secrets and embedded credentials in stored files and archives. |
| NHI-04 — Secret Sprawl and Discovery | Recursive scanning addresses secrets hidden in nested files, archives, and backups. | |
| Recommendation — Scan extracted blob contents for secrets and verify suspected credentials before escalating. Expand archives recursively and scan every extracted member for hidden secrets. | ||
| CIS Controls v8 | 8 — Audit Log Management | Scan workflows need evidence of what was inspected and which findings were verified. |
| 3 — Data Protection | Blob storage often contains sensitive files and backups that must be searched for secret exposure. | |
| Recommendation — Log scan scope, archive expansion, and verification results for each blob. Classify blob content and prioritise scanning of archives, exports, and backups. | ||
| NIST CSF 2.0 | PR.DS — Data Security | Scanning blob contents and archives is a data-security control against secret exposure. |
| Recommendation — Apply data-security controls to locate and remediate secrets stored in blobs. | ||
Practitioner Guidance
What to verify: Confirm that the scanner is unpacking common archive formats, traversing nested archives safely, and scanning extracted members as first-class files. If it only reads top-level objects, it is not sufficient for blob repositories that contain exported systems, backups, or packaged data.
What to measure: Track the ratio of verified findings to raw matches, plus the number of archive layers successfully expanded per scan. A healthy programme should show lower false-positive rates after verification and no unexplained gaps in archive coverage.
Common mistake: Treating “scanned the container” as equivalent to “scanned the content.” For Blob Storage, the container is often the least interesting part; the real exposure lives inside the embedded file tree.
Practitioner takeaway: The safest workflow is content expansion first, secret detection second, and provider-backed verification third, because that sequence catches embedded credentials without drowning the team in untrusted matches.
Related resources from NHI Mgmt Group
- How should security teams scan for secrets in deleted or private GitHub commits without missing hidden attack surface?
- How should security teams scan API workspaces for leaked secrets without missing the places people actually store them?
- How should security teams govern Azure storage account secrets?
- How should teams reduce Azure Key Vault costs without weakening secrets security?
Deepen Your Knowledge
Reviewed and updated by the NHIMG editorial team on September 19, 2026.
NHI Mgmt Group — the #1 independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org
