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Rare Not Random Using Token Efficiency for Secrets Scanning
Researcher proposes token efficiency (string length divided by BPE token count) as a better post-regex filter than entropy for secrets scanning, validated on CredData.
The post explores whether Byte-Pair Encoding tokenization can replace Shannon entropy as the primary filter for candidate secrets captured by regex in tools like Gitleaks. It defines 'token efficiency' as string length divided by token count under the cl100k_base tokenizer; secret-like strings such as GitHub tokens tokenize into many small tokens and score low, while natural text scores high. Evaluating labeled secrets from the CredData dataset shows a usable separation, with roughly 2.5 suggested as a minimum cutoff versus Gitleaks' 3.5 entropy threshold. The technique is positioned as a post-regex filtering step rather than a standalone detector.
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Open-source secrets scanning tool Sift hunts credentials in Microsoft 365, Slack, and Jira
Stratus Security open-sourced Sift, a CLI secrets scanner covering Active Directory, SharePoint, Teams, Slack, Jira, and Confluence, outperforming Snaffler in benchmarks.
Stratus Security released Sift, a free open-source command line tool that hunts passwords, API keys, and sensitive data across local disks, Windows shares, Active Directory, SharePoint, OneDrive, Teams, Slack, Jira, and Confluence. In the firm's benchmarks, Sift scanned 250,000 files in 10.61 seconds versus Snaffler's 25.48 and averaged 92 MiB memory versus Snaffler's 337 MiB. Optional false-positive filtering runs through a local language model via Ollama, and scans write checkpoints so interrupted runs resume. The tool found thousands of credentials in Jira ticket comments that prior pentesting had missed.
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Mapping out your unknown: A threat hunter’s guide to GitHub
Datadog Security Labs publishes a threat-hunting guide with audit-log queries to detect GitHub token theft, device code phishing, and source code exfiltration.
Datadog's threat-hunting guide covers GitHub audit log queries for detecting compromised accounts, stolen personal access tokens, and malicious OAuth app authorizations. Attackers typically obtain credentials through phishing, credential stuffing, leaked secrets, or device code phishing, then map private repositories, exfiltrate source code, and pivot into connected cloud and CI/CD environments. The guide maps detections to MITRE techniques like T1078 and T1528 and documents GitHub logging quirks affecting attribution, token metadata, and visibility fields.
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UAT-10608: Inside a large-scale automated credential harvesting operation targeting web applications
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Hackers target exposed Vite dev servers to steal AWS, Azure secrets
Mass scanning campaign exploits CVE-2026-39364 in exposed Vite dev servers to steal AWS, Azure, and Terraform credentials.
F5 honeypots detected over 800 attacks and roughly 32,000 events in a month against internet-exposed Vite development servers, abusing CVE-2026-39364 (file access control bypass in Vite 7.1.0-7.3.2 and 8.x before 8.0.5) via parameters like ?raw and ?import&raw. Attackers used extensive wordlists to harvest .env files, AWS/Azure credentials, Terraform state, and /proc/self/environ, with double-encoded traversal to bypass WAFs. The same IPs also leveraged older Vite flaws CVE-2025-30208, actively-exploited CVE-2025-31125, and CVE-2024-45811, primarily from US, Belgium, and Netherlands using Google Cloud ranges.
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