# Unit 42 Palo Alto Networks This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Atomic macOS (AMOS) Stealer Activity DevFeed: [Atomic macOS (AMOS) Stealer Activity]() Original publisher: [Read original article]() Author: Bradley Duncan Published: 2026-09-16T10:00:06Z Content type: article Language: en Sources: [Unit 42]() Topics: [Malware](), [Aeternum](), [macOS](), [sensitive data](), [Zsh](), [ClickFix](), [cURL]() Tags: [ads](), [clickfix](), [credentials](), [cryptocurrency](), [curl](), [general](), [insights](), [macos](), [malware](), [sensitive-data](), [threat-intelligence](), [unit-42](), [zsh]() ### AI overview This article analyzes a laboratory-generated Atomic macOS (AMOS) stealer infection observed on Aug. 5, 2026. It describes a deceptive macOS toolkit installation page that led users to paste a command into Terminal, retrieving a Zsh script containing an encoded compressed payload and a follow-up script designed to run a Mach-O binary. AMOS targets macOS and can exfiltrate system information, login credentials, and sensitive data from applications including browsers and cryptocurrency wallets. ### Source excerpt Modern macOS malware uses deceptive setup guides to steal credentials and sensitive user data. Learn how to identify and block these threats. The post Atomic macOS (AMOS) Stealer Activity appeared first on Unit 42. ## Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection DevFeed: [Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection]() Original publisher: [Read original article]() Author: Osher Jacob Published: 2026-09-14T10:00:01Z Content type: article Language: en Sources: [Unit 42]() Topics: [AWS CloudTrail](), [Cloud](), [threat detection](), [Threat Research](), [SIEM, Security, Observability](), [Machine learning](), [Algorithms](), [SQL](), [IAM](), [identity and access management](), [Amazon Web Services]() Tags: [algorithms](), [amazon-web-services-aws](), [analysis](), [aws-cloudtrail](), [cloud](), [cloud-cybersecurity-research](), [cloud-detection](), [devops](), [iam](), [identity-and-access-management](), [logs](), [machine-learning](), [post](), [sql](), [threat-detection](), [threat-research]() ### AI overview This article presents a behavioral clustering model for mapping cloud identities to functional roles using activity patterns from audit logs. It applies unsupervised machine learning with UMAP and HDBSCAN to data from more than 40,000 identities across 125 cloud environments, and shows how the resulting map can support automated threat detection. The article also explains how lightweight heuristics extracted from the map can classify identities at scale using standard SQL, reducing the need for continuous resource-intensive machine learning pipelines. ### Source excerpt We designed a behavioral clustering model to map cloud identity roles from audit logs, enabling continuous threat detection using standard SQL queries. The post Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection appeared first on Unit 42. ## The Machine With Many Faces: Post-Exploitation Identity Misuse in SPIFFE/SPIRE DevFeed: [The Machine With Many Faces: Post-Exploitation Identity Misuse in SPIFFE/SPIRE]() Original publisher: [Read original article]() Author: Eviatar Garzi Published: 2026-09-10T10:00:43Z Content type: article Language: en Sources: [Unit 42]() Topics: [Kubernetes]() Tags: [api](), [containers](), [cryptographic](), [identity](), [json](), [kubernetes](), [linux](), [malware](), [node](), [open-source](), [research](), [secrets](), [spiffe](), [spire](), [spoof](), [spoofing](), [threat-research](), [tool]() ### AI overview Research on a post-exploitation technique in which root access to a Kubernetes node can let an attacker spoof cgroup metadata used by SPIRE workload attestation, impersonate co-located workloads, and obtain SVIDs. ### Source excerpt Learn how root access on a compromised K8s node allows attackers to utilize SPIFFE/SPIRE metadata to spoof and harvest co-located workload identities. The post The Machine With Many Faces: Post-Exploitation Identity Misuse in SPIFFE/SPIRE appeared first on Unit 42. ## Untracked Nightmares: The Threats Hiding Behind Commodity Infrastructure DevFeed: [Untracked Nightmares: The Threats Hiding Behind Commodity Infrastructure]() Original publisher: [Read original article]() Author: Rem Dudas Published: 2026-09-09T10:00:55Z Content type: article Language: en Sources: [Unit 42]() Topics: [ARKTunnel](), [backdoor]() Tags: [arktunnel](), [backdoor](), [c2](), [cl-cri-1171](), [cybercrime](), [docro-hijacker](), [gaming](), [malware](), [pay-per-install](), [payload](), [remote-access-trojan](), [threat-research](), [youtube]() ### AI overview An investigation of the CL-CRI-1171 cybercrime campaign describes how YouTube gaming lures and SEO poisoning delivered malware through a custom loader. It covers Docro Hijacker, ARKTunnel, and the Insomnia remote access Trojan. ### Source excerpt An investigation into how cybercriminals used YouTube gaming lures and SEO poisoning to deliver multi-payload malware to enterprise networks. The post Untracked Nightmares: The Threats Hiding Behind Commodity Infrastructure appeared first on Unit 42. ## Attackers Expose Ongoing AI Tool Use Targeting Organizations in Latin America DevFeed: [Attackers Expose Ongoing AI Tool Use Targeting Organizations in Latin America]() Original publisher: [Read original article]() Author: Reese Lewis and Sara McBroom Published: 2026-09-03T10:00:58Z Content type: article Language: en Sources: [Unit 42]() Topics: [Language models](), [AI Chat](), [Incident response]() Tags: [agentic-ai](), [ai](), [chatgpt](), [cl-cri-1131](), [cl-cri-1163](), [claude-code](), [data](), [financial-sector](), [go](), [large-language-models-llms](), [malware](), [nextchat](), [operations](), [phishing](), [shipping-and-transportation](), [socks5](), [socktz](), [threat-research]() ### AI overview The article examines two ongoing intrusion and data-exfiltration campaigns targeting organizations in Latin America. It describes attackers using commercial large language models, proxy infrastructure, phishing, remote-access malware, and operational tooling. ### Source excerpt Explore how attackers targeting Latin American entities use AI for data exfiltration and how basic OpSec errors allow defenders to disrupt operations. The post Attackers Expose Ongoing AI Tool Use Targeting Organizations in Latin America appeared first on Unit 42. ## An AI-Assisted Cyber Attack: Inside a Unit 42 Investigation DevFeed: [An AI-Assisted Cyber Attack: Inside a Unit 42 Investigation]() Original publisher: [Read original article]() Author: Renzon Cruz, Nicolas Bareil, Eric Semaan and Omar Jbari Published: 2026-09-02T10:00:46Z Content type: article Language: en Sources: [Unit 42]() Topics: [Security Attacks](), [Large Language Model](), [CI/CD]() Tags: [agentic](), [agentic-ai](), [ai](), [ai-agents](), [attacks](), [autonomous](), [breach](), [ci-cd](), [enterprise](), [frontier-ai](), [general](), [insights](), [llm](), [secrets](), [security](), [threat-research]() ### AI overview An investigation of a ransom attack in which a human attacker used AI agents and frontier models to automate intrusion, reconnaissance, credential theft, and CI/CD pipeline abuse against an enterprise network. ### Source excerpt Using autonomous AI agents, an attacker breached an enterprise network in a matter of hours. Understand how to address and defend against agentic attacks. The post An AI-Assisted Cyber Attack: Inside a Unit 42 Investigation appeared first on Unit 42. ## Spring Ring: An Inside Look at Voice Phishing Campaigns in Microsoft Teams DevFeed: [Spring Ring: An Inside Look at Voice Phishing Campaigns in Microsoft Teams]() Original publisher: [Read original article]() Author: Noam Sala Published: 2026-08-31T10:00:36Z Content type: article Language: en Sources: [Unit 42]() Topics: [Social engineering](), [Malware](), [remote access software](), [Microsoft](), [Cloaked Ursa](), [Entra ID](), [Incident response]() Tags: [attacks](), [cloaked-ursa](), [enterprise](), [entra-id](), [incident-response](), [malware](), [microsoft](), [microsoft-teams](), [payload](), [phishing](), [powershell](), [remote-access-trojan](), [social-engineering](), [spoof](), [threat-research](), [vishing](), [voice]() ### AI overview Spring Ring is a coordinated social engineering campaign that used external Microsoft Teams accounts and voice phishing to impersonate IT help desk staff. The operation targeted more than 150 employees across at least 10 companies and attempted to deliver remote monitoring and management tools or custom malware. A more advanced variant escalated to an NTLM relay attack against an organization's domain controller. ### Source excerpt Learn how the Spring Ring campaign abuses Microsoft Teams and voice phishing to deploy malware and target enterprise domain controllers. The post Spring Ring: An Inside Look at Voice Phishing Campaigns in Microsoft Teams appeared first on Unit 42. ## Perturbation Probing: A New Diagnostic for the Fragility of LLM Safety DevFeed: [Perturbation Probing: A New Diagnostic for the Fragility of LLM Safety]() Original publisher: [Read original article]() Author: Tony Li, Hongliang Liu and Yuhao Wu Published: 2026-08-28T22:00:07Z Content type: article Language: en Sources: [Unit 42]() Topics: [Large Language Model](), [ai safety](), [Machine Learning, Security Attacks](), [Security](), [Artificial Intelligence](), [Reinforcement learning](), [human feedback]() Tags: [ai](), [ai-safety](), [benchmark](), [benchmarks](), [external](), [general](), [insights](), [internals](), [jailbreak](), [llm](), [llms](), [model](), [optimization](), [research](), [safety](), [security]() ### AI overview The article presents perturbation probing, a low-cost method for identifying neurons causally responsible for targeted behaviors in aligned large language models. It reports that very small neuron subsets control refusal or false-agreement behaviors, suggesting that LLM safety can be fragile and concentrated rather than broadly distributed. ### Source excerpt New research reveals that AI safety refusal lives in a thin neural layer, highlighting the critical need for external, multi-layered security. The post Perturbation Probing: A New Diagnostic for the Fragility of LLM Safety appeared first on Unit 42. ## The State of AI-Enabled Malware August 2026: From Brand Abuse to Agentic Execution DevFeed: [The State of AI-Enabled Malware August 2026: From Brand Abuse to Agentic Execution]() Original publisher: [Read original article]() Author: Sara McBroom Published: 2026-08-25T10:00:57Z Content type: article Language: en Sources: [Unit 42]() Topics: [Malware](), [Artificial Intelligence](), [Security](), [Endpoint Security & XDR](), [VirusTotal](), [dataset](), [data](), [ChatGPT](), [ransomware](), [Cryptocurrency]() Tags: [agentic](), [ai](), [analysis](), [article](), [backdoor](), [bitcoin](), [code](), [cryptocurrency](), [data](), [dll-hijacking](), [malware](), [ransomware](), [research](), [sandbox](), [security](), [threat-research](), [virustotal]() ### AI overview Unit 42 analyzes 405 malware samples incorporating AI through mechanisms such as brand impersonation, LLM-generated code, and agentic execution loops. The research finds that most samples remain proof-of-concept or sandbox activity, while existing behavioral detection, cloud sandboxing, and endpoint analytics can detect the threats that reach operational environments. ### Source excerpt Explore Unit 42 research on AI-enabled malware. Learn how existing behavioral detection and endpoint analytics stop AI-authored code before execution. The post The State of AI-Enabled Malware August 2026: From Brand Abuse to Agentic Execution appeared first on Unit 42. ## Connecting the Dots: Securing the Overlooked Corners of the Software Development Lifecycle (SDLC) Supply Chain DevFeed: [Connecting the Dots: Securing the Overlooked Corners of the Software Development Lifecycle (SDLC) Supply Chain]() Original publisher: [Read original article]() Author: Yaron Avital Published: 2026-08-21T23:00:21Z Content type: article Language: en Sources: [Unit 42]() Topics: [sdlc](), [Security](), [Application Security](), [CI/CD](), [GitHub Actions](), [npm](), [Bun](), [Python](), [Claude Code](), [vs-code](), [Claude](), [Ethereum]() Tags: [blockchain](), [c2](), [chaindrop](), [ci-cd](), [claude-code](), [general](), [github-actions](), [insights](), [malware](), [npm-packages](), [persistence](), [python](), [sdlc](), [security](), [software-supply-chain-attack](), [supply-chain](), [vs-code]() ### AI overview Unit 42 describes how software supply-chain attackers are targeting developer tools, CI/CD pipelines, accounts, packages, setup scripts and developer environments before software reaches production. It examines the ChainDrop npm worm, which used malicious preinstall hooks, a Bun runtime, an obfuscated payload, Python-based memory theft, stolen tokens and secrets, self-propagation, persistence in VS Code and Claude Code, and Ethereum-managed command-and-control infrastructure. ### Source excerpt Attackers are targeting CI/CD pipelines and developer tools instead of application code, requiring total SDLC visibility and strict security controls The post Connecting the Dots: Securing the Overlooked Corners of the Software Development Lifecycle (SDLC) Supply Chain appeared first on Unit 42. ## Identity Abuse Through Trusted Communication Channels DevFeed: [Identity Abuse Through Trusted Communication Channels]() Original publisher: [Read original article]() Author: Bill Batchelor Published: 2026-08-20T10:00:25Z Content type: article Language: en Sources: [Unit 42]() Topics: [Security](), [Authentication](), [Social engineering](), [Software as a service](), [Incident response]() Tags: [authentication](), [credential-theft](), [identity](), [identity-theft](), [incident-response](), [malware](), [mfa](), [phishing](), [remote-access-software](), [saas](), [security](), [social-engineering](), [threat-research]() ### AI overview Unit 42 examines how attackers abuse trusted enterprise communication and collaboration platforms for identity phishing, impersonation, credential theft, malware delivery and social engineering. The article describes how compromised identities can make malicious activity appear legitimate within authenticated collaboration sessions and offers recommendations for detecting and defending against these attacks. ### Source excerpt Unit 42 details how attackers exploit enterprise collaboration tools for identity phishing and credential theft. Discover key defense strategies. The post Identity Abuse Through Trusted Communication Channels appeared first on Unit 42. ## Threat Brief: Mitigating Large-Scale Credential Attacks (Updated August 18) DevFeed: [Threat Brief: Mitigating Large-Scale Credential Attacks (Updated August 18)]() Original publisher: [Read original article]() Author: Unit 42 Published: 2026-08-18T19:05:33Z Content type: article Language: en Sources: [Unit 42]() Topics: [Credential theft](), [password spraying](), [MFA](), [Microsoft](), [Incident response]() Tags: [credential-based-attacks](), [credential-theft](), [general](), [high-profile-threats](), [identity](), [incident](), [incident-response](), [mfa](), [microsoft](), [password-spraying](), [thehatman]() ### AI overview This threat brief examines large-scale credential attacks, including password spraying campaigns and claimed credential theft from Microsoft Entra tenants. It provides guidance for identifying suspicious login activity, auditing remote access logs, and hardening internet-exposed edge devices. ### Source excerpt In August 2026, the actor TheHatman claimed to have stolen large volume of credentials from organizations' Microsoft Entra tenants. We provide guidance on mitigating large-scale credential attacks. The post Threat Brief: Mitigating Large-Scale Credential Attacks (Updated August 18) appeared first on Unit 42. ## Kimwolf v7: An Evolution of the Kimwolf Botnet DevFeed: [Kimwolf v7: An Evolution of the Kimwolf Botnet]() Original publisher: [Read original article]() Author: Asher Davila, Chris Navarrete and Doel Santos Published: 2026-08-11T10:00:16Z Content type: article Language: en Sources: [Unit 42]() Topics: [Kimwolf v7](), [Android](), [DDoS](), [Internet of things](), [C2](), [Ethereum Name Service (ENS)](), [Malware](), [Cybercrime](), [Ethereum](), [Blockchain](), [Routing (disambiguation)](), [Threat Hunting & Intel]() Tags: [android](), [android-apk](), [blockchain](), [c2](), [ddos](), [devices](), [ethereum](), [http](), [iot-botnets](), [kimwolf-v7](), [linux](), [malware](), [network](), [networks](), [resilience](), [routing](), [rpc](), [spoofing](), [threat-research]() ### AI overview Kimwolf v7 is an Android and IoT botnet variant that adds HTTP/2-based DDoS flooding with browser fingerprinting, Ethereum Name Service resolution for C2 addresses, and Tor-backed routing to improve infrastructure resilience. The article also describes its targeting of Android TV devices and exploitation of unauthenticated ADB instances. ### Source excerpt Discover how Kimwolf v7 targets Android IoT devices with HTTP/2 DDoS fingerprinting, Ethereum ENS C2 resolution and Tor backup routing. The post Kimwolf v7: An Evolution of the Kimwolf Botnet appeared first on Unit 42. ## The Permanent Threat: Analyzing Aeternum's Blockchain-Based C2 Operations and Communications DevFeed: [The Permanent Threat: Analyzing Aeternum's Blockchain-Based C2 Operations and Communications]() Original publisher: [Read original article]() Author: Chris Navarrete, Sai Sathvik Ruppa and Haozhe Zhang Published: 2026-08-10T22:00:02Z Content type: article Language: en Sources: [Unit 42]() Topics: [Aeternum](), [C++](), [Firewall]() Tags: [aeternum](), [analysis](), [blockchain](), [c-plus-plus](), [c2](), [infection-chain](), [json](), [malware](), [python](), [rpc](), [telegram](), [threat-research](), [xmrig](), [xor]() ### AI overview An analysis of the Aeternum botnet loader, which uses Polygon blockchain smart contracts and public RPC endpoints for decentralized command-and-control. It also examines related Python malware using the Telegram API and a blended threat involving XWorm RAT, XMRig, and data exfiltration. ### Source excerpt Analysis of the Aeternum botnet loader, a threat leveraging Polygon blockchain smart contracts for decentralized C2 infrastructure and payload execution. The post The Permanent Threat: Analyzing Aeternum's Blockchain-Based C2 Operations and Communications appeared first on Unit 42. ## Inside the Modern SOC: The Identity Front Door DevFeed: [Inside the Modern SOC: The Identity Front Door]() Original publisher: [Read original article]() Author: Sharon Maydar Published: 2026-08-07T23:00:01Z Content type: article Language: en Sources: [Unit 42]() Topics: [Incident response](), [MFA](), [Vulnerabilities]() Tags: [ai](), [attacks](), [authentication](), [credential-theft](), [identity](), [incident-response](), [inside-the-modern-soc](), [insights](), [mfa](), [phishing](), [soc](), [social-engineering](), [unit-42-incident-response-report](), [vulnerabilities]() ### AI overview The article examines identity-based initial access, including credential theft, MFA manipulation, session hijacking, phishing, and social engineering. It describes how attackers expand access through persistence, privilege escalation, and lateral movement, challenging SOC teams to correlate signals across environments. ### Source excerpt Identity-based attacks drive 90% of incidents. Learn how modern attackers exploit identities and what SOC leaders can do to respond. The post Inside the Modern SOC: The Identity Front Door appeared first on Unit 42. ## ChainDrop: Inside a Self-Propagating npm Worm DevFeed: [ChainDrop: Inside a Self-Propagating npm Worm]() Original publisher: [Read original article]() Author: Unit 42 Published: 2026-08-06T22:26:39Z Content type: article Language: en Sources: [Unit 42]() Topics: [ChainDrop](), [npm](), [Malware](), [C2](), [Ethereum](), [GitHub Actions](), [GitHub](), [CI/CD](), [Security]() Tags: [blockchain](), [c2](), [chaindrop](), [ci](), [claude-code](), [developer-tooling](), [ethereum](), [github](), [github-actions](), [high-profile-threats](), [infrastructure](), [malware](), [security](), [ssh](), [supply-chain](), [tokens]() ### AI overview This article analyzes ChainDrop, a self-propagating npm worm that infected more than 400 packages and threatened developer workstations, CI pipelines, cloud environments and downstream users. It describes credential and token theft, GitHub Actions runner memory extraction, package republishing, persistence through developer and AI coding tools, blockchain-based C2 resolution, and C2 reconfiguration through an Ethereum transaction. ### Source excerpt Analysis of ChainDrop, an npm supply chain worm extracting GitHub Actions runner secrets and using Ethereum smart contracts for C2 routing. The post ChainDrop: Inside a Self-Propagating npm Worm appeared first on Unit 42. ## Token Jacking: Cybercriminals Could Be Stealing Your AI Resources DevFeed: [Token Jacking: Cybercriminals Could Be Stealing Your AI Resources]() Original publisher: [Read original article]() Author: Unit 42 Published: 2026-08-06T10:00:49Z Content type: article Language: en Sources: [Unit 42]() Topics: [token jacking](), [ai security](), [API keys](), [Large language models (LLMs)](), [Authentication](), [transfer stations]() Tags: [ai](), [ai-api](), [ai-gateway](), [ai-security](), [api-keys](), [authentication](), [large-language-models-llms](), [malware](), [npm-packages](), [obfuscation](), [security](), [threat-research](), [token-jacking](), [transfer-stations]() ### AI overview The article explains how criminals steal developers' AI API keys and use the resulting tokens to consume costly language-model resources, causing rapid financial losses. It outlines the role of authentication, automated access keys, token-based billing, and weak billing controls, and recommends security hygiene and AI protection measures. ### Source excerpt Discover how attackers hijack AI tokens to fuel gray market transfer stations by stealing developer API keys. The post Token Jacking: Cybercriminals Could Be Stealing Your AI Resources appeared first on Unit 42.