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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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SpyCloud 2026 Identity Threat Report Finds Non-Human Identities Are Now the Leading Path into the Enterprise
SpyCloud survey of 750 security leaders finds compromised non-human identities are the top enterprise entry point, yet only 36% monitor them.
The 2026 Identity Threat Report surveyed 750 cybersecurity leaders at organizations with 500+ employees across North America and Europe. Compromised non-human identities (31%) were the most cited primary attacker entry point, nearly double phishing (17%), while only 36% of organizations monitor AI agents, service accounts and API keys. 68% of respondents reported identity-based events, averaging eight each, and 91% use AI tools but only 56% have formal governance over their privileges.
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Weak IAM affects up to 98% of cloud environments
Intruder's 2026 Cloud Security Index finds weak IAM controls affect up to 98% of cloud environments across AWS, Azure, and Google Cloud.
Intruder's 2026 Cloud Security Index report analyzed cloud misconfigurations across midmarket and enterprise environments, finding weak IAM controls and missing logging affected 80% to 98% of accounts across all three major providers. AWS recorded the highest prevalence in five of six categories, including exposed services at 76% versus 8% on Google Cloud. IAM weaknesses worsen with scale, affecting 87% of SMEs, 95% of midmarket organizations, and 98% of large enterprises, while remediation times peak at 35 days for organizations with 1,000 to 5,000 employees.
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Phishing Research Challenges Conventional Security Awareness Testing
Pistachio's 2.47 million phishing simulations across 1,200 organizations show click rates alone mislead, with 30% of IT staff clicking and leak rates more predictive.
Between June 2025 and May 2026, Pistachio sent 2.47 million simulated phishing attempts to more than 123,000 employees at over 1,200 organizations, analyzing click, credential-leak and reporting behavior. Click rates ranged from 26% in Design to 41% in Construction; 30% of tech development and IT staff clicked at least once, while financial services were the most resilient sector. The report argues that click rate alone creates a false sense of security and that combined click, leak and report trends are better resilience indicators.
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Getting ahead of ‘harvest-now-decrypt-later’: Post-quantum cryptography planning
Opinion piece urges organizations to begin post-quantum cryptography migration now, citing harvest-now-decrypt-later risk and NIST deadlines.
CSO Online outlines why harvest-now-decrypt-later makes long-lived sensitive data a current risk even before quantum computers exist. It cites NIST IR 8547 timelines deprecating RSA-2048 and ECC P-256 by 2030 and removing them by 2035, finalized FIPS standards ML-KEM, ML-DSA, and SLH-DSA, upcoming FN-DSA (FIPS 206), NSA requirements for national security systems from 2027, and UK NCSC phased guidance through 2035. The author recommends cryptographic discovery, crypto-agility, and prioritizing long-confidentiality data and TLS endpoints.
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Your Cloud Security Checklist Doesn't Work the Way You Think It Does
Intruder's 2026 Cloud Security Index found misconfiguration risk profiles differ sharply across AWS, Azure, and Google Cloud across 3,000 organizations.
Intruder analyzed misconfiguration data from 3,000 organizations across AWS, Azure, and Google Cloud for its 2026 Cloud Security Index. Weak IAM controls and missing logging affected 80-98% of accounts regardless of provider, while exposed services ranged from 76% on AWS to just 8% on Google Cloud. Top issues included S3 buckets without HTTPS enforcement (87% of AWS accounts), Entra ID users without MFA (55% of Azure accounts), and missing OS Login MFA (77% of Google Cloud accounts). Weak IAM prevalence rose with organization size, from 87% at SMEs to 98% at large enterprises, and midmarket organizations took the longest to remediate at 35 days on average.
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AI is changing what Salesforce security needs to govern
WithSecure's Trust Mapping paper proposes a framework for governing trust relationships across Salesforce workflows, AI agents, integrations and connected SaaS systems.
WithSecure's paper 'Navigating Trust in the Modern Salesforce Ecosystem' introduces a Trust Mapping Framework spanning five domains: entities, information, connections, actions and system outcomes. It applies to Salesforce, Agentforce, Headless 360, third-party SaaS and AI-assisted workflows where users, AI agents, APIs and integrations form trust relationships. A Discovery step maps relationships, a Governance step assesses, restricts or retires them, and the paper defines 'trust drift' such as stale credentials, excessive access and unvalidated AI recommendations.
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Introducing Unit 42’s Attribution Framework
Unit 42 releases its Attribution Framework, a systematic method using Diamond Model and Admiralty scores to attribute activity clusters to named threat actors.
Palo Alto Networks' Unit 42 introduced a structured framework for threat actor attribution built on the Diamond Model of Intrusion Analysis and Admiralty reliability/credibility scoring. The framework tracks activity at three levels: activity clusters (named CL-STA, CL-CRI, CL-UNK, or CL-MIX), temporary threat groups, and named threat actors using the constellation naming schema. Analysts score evidence across TTPs, tooling, malware code, OPSEC, infrastructure, timelines, and victimology to decide when to merge or elevate clusters, avoiding premature group naming.
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Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection
Unit 42 clusters behavior of 40,000+ AWS identities from 125 cloud environments to map functional roles and enable lightweight SQL-based detection.
Palo Alto Unit 42 built an unsupervised behavioral clustering model using UMAP and HDBSCAN on AWS CloudTrail logs to map cloud identities to functional roles such as administrators, backup services, security tooling and DevOps. The study analyzed over 40,000 identities across 125 cloud environments over two months. The researchers show that heuristics extracted from the clustering map can be implemented in standard SQL, enabling role classification at scale without running a continuous ML pipeline. The methodology extends to audit logs from other cloud providers, SaaS and Kubernetes.
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When the Whole Company Adopts AI: What It Does to Your SOC
Analysis of 16.9 million SOC alerts finds AI-related alerts at 0.43%, growing 685% since February, with 94.1% noise and 0.02% real attacks.
A review of roughly 16.9 million SOC alerts found about 73,000 (0.43%) were AI-related, a share that grew 685% between February and June 2026. Of AI-related alerts, 94.1% were noise, 5.8% genuine risks, and 0.02% real attacks; 79.8% received benign verdicts, 81.7% were automatically suppressed, and only 5.4% reached a human analyst. The only confirmed attacks were phishing campaigns that weaponized AI brand names as lures, while developer coding agents spawning shells and reading credential stores routinely tripped detections written before AI agents existed.
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NHIs Now the Number One Corporate Entry Point for Hackers
SpyCloud survey finds non-human identities like AI agents and API keys were the primary entry point in 31% of intrusions, nearly double phishing.
SpyCloud's Identity Threat Report, based on a survey of 750 security leaders at organizations with 500+ employees, found non-human identities caused 31% of intrusions versus 17% for social engineering. Only 36% of organizations actually monitor NHIs although 95% believe they have adequate visibility into them. Some 68% of respondents suffered an identity-based event, with NHI-related misuse at 42%, and organizations able to see stolen session cookies reported identity incidents at a lower rate (37% vs 50%).
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