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Information Technology/IT

Breach intelligence, attack campaigns, and threat reports targeting the Information Technology/IT sector.

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Information Technology/IT Threat Reports

Showing 2833–2844 / 3797 reports
How Attackers Used Python and Cloudflare to Deploy AsyncRAT in 2024
Financial Services10 months ago

How Attackers Used Python and Cloudflare to Deploy AsyncRAT in 2024

In mid-2024, cybersecurity researchers uncovered a sophisticated phishing campaign in which threat actors leveraged Python scripts and the Cloudflare platform to distribute the AsyncRAT remote access trojan (RAT). Attackers crafted convincing email lures that enticed recipients to execute supplied Python scripts, which subsequently contacted Cloudflare infrastructure to retrieve further payloads. The use of legitimate services such as Cloudflare enabled the attackers to bypass conventional security controls, effectively concealing command-and-control traffic and deploying malware without immediate detection. The campaign facilitated remote access to victim systems, data exfiltration, and the potential for lateral movement within compromised networks. This incident underscores a continuing trend in which malicious actors abuse reputable cloud and open source ecosystems to deliver payloads and evade traditional defenses. Organizations across sectors must remain vigilant as threat groups increasingly weaponize trusted platforms and novel delivery mechanisms.

Medium impact

Kill Chain

ICInitial Compromise(high)
PEPrivilege Escalation(medium)
LMLateral Movement(medium)
C&CCommand & Control(high)
EExfiltration(high)
IImpact(medium)
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Supply Chain RCE Threats in Leading AI/ML Python Libraries (2025-2026)

Supply Chain RCE Threats in Leading AI/ML Python Libraries (2025-2026)

In January 2026, significant remote code execution (RCE) vulnerabilities were disclosed across leading open-source AI/ML Python libraries maintained by NVIDIA (NeMo), Salesforce (uni2TS), and Apple (ml-flextok). Attackers could craft malicious model files with compromised metadata; upon loading these files via vulnerable libraries, arbitrary code would execute on the host system. These vulnerabilities stemmed from insecure use of third-party serialization/configuration functions—primarily Hydra's instantiate()—without proper validation, enabling supply chain attacks on widely distributed AI models, particularly via public repositories such as HuggingFace. No in-the-wild exploits were confirmed before public disclosure; however, the affected vendors coordinated prompt patches and mitigations throughout 2025. This incident illustrates a growing trend of software supply chain threats cascading into the AI/ML ecosystem. With increased adoption of AI and routine sharing of pretrained models, even safe-seeming formats may introduce unseen risks, underscoring the urgency for security controls, vigilance in model sourcing, and rapid adaptation of secure-by-design principles for both model creators and consumers.

Medium impact

Kill Chain

ICInitial Compromise(high)
PEPrivilege Escalation(medium)
LMLateral Movement(medium)
C&CCommand & Control(medium)
EExfiltration(medium)
IImpact(medium)
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Critical Ni8mare Flaw Exposes 60,000+ n8n Instances to Remote Exploitation

Critical Ni8mare Flaw Exposes 60,000+ n8n Instances to Remote Exploitation

In January 2026, a critical vulnerability tracked as CVE-2026-21858, dubbed "Ni8mare," was disclosed in n8n, the widely-used open-source workflow automation platform. The flaw, rooted in improper input validation of form file elements, allows unauthenticated remote attackers to seize control of exposed n8n instances by exploiting online workflows. This exposure places sensitive credentials, API keys, and business data at risk across nearly 60,000 instances, with especially high concentrations in the US and Europe. The vulnerability can lead to credential theft, privilege escalation, and even arbitrary command execution, depending on instance configuration. This incident is highly relevant given the broad adoption of low-code and automation platforms in AI and DevOps workflows, making them attractive targets for attackers seeking lateral movement or data exfiltration. The ongoing exposure of thousands of n8n servers underscores the urgent need for robust vulnerability management and secure configuration in automation environments.

Medium impact

Kill Chain

ICInitial Compromise(high)
PEPrivilege Escalation(medium)
LMLateral Movement(medium)
C&CCommand & Control(medium)
EExfiltration(medium)
IImpact(medium)
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Endesa 2024 Data Breach: Key Lessons for Energy Sector Security

Endesa 2024 Data Breach: Key Lessons for Energy Sector Security

In May 2024, Spanish energy giant Endesa, alongside its subsidiary Energía XXI, disclosed a data breach following unauthorized access to its internal systems by unknown attackers. The incident exposed sensitive contract-related information and personal details belonging to Endesa customers, although the company stated that no financial data was compromised. Endesa responded by promptly notifying affected clients, securing compromised systems, and initiating an investigation with law enforcement and the Spanish data protection authority. The breach underscores the growing targeting of critical infrastructure providers, where even non-financial data leaks can erode customer trust and regulatory posture. This incident is particularly relevant as critical infrastructure companies face heightened risk from threat actors leveraging lateral movement and data exfiltration techniques. With the energy sector increasingly interconnected and digitalized, organizations must prioritize zero trust strategies and robust monitoring to meet evolving compliance and regulatory demands.

High impact

Kill Chain

ICInitial Compromise(medium)
PEPrivilege Escalation(medium)
LMLateral Movement(medium)
C&CCommand & Control(low)
EExfiltration(medium)
IImpact(high)
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Target 2026 Source Code and Git Server Breach Highlights DevSecOps Urgency
Retail Industry10 months ago

Target 2026 Source Code and Git Server Breach Highlights DevSecOps Urgency

In January 2026, Target Corporation experienced a suspected breach of its internal development infrastructure when unknown hackers claimed to have stolen and begun selling portions of Target's private source code. The threat actors posted sample repositories from Target’s Git server on Gitea and advertised access to a much larger (860 GB) archive for sale on dark web forums. The exposed repositories contained sensitive developer documentation, code, and referenced Target engineers and internal systems. Target responded by removing the exposed Gitea repositories and taking its developer Git server offline shortly after the breach was reported. This incident highlights the increasing risk of software supply chain attacks, especially as threat actors target source code and development assets. The breach reflects broader trends of cybercriminals exploiting version control servers and developer tools to exfiltrate proprietary code, putting organizations’ intellectual property, security, and regulatory posture at risk.

High impact

Kill Chain

ICInitial Compromise(medium)
PEPrivilege Escalation(low)
LMLateral Movement(low)
C&CCommand & Control(low)
EExfiltration(high)
IImpact(high)
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CISA Orders Critical Patching After Gogs Zero-Day RCE Attacks Hit Hundreds of Servers

CISA Orders Critical Patching After Gogs Zero-Day RCE Attacks Hit Hundreds of Servers

In January 2026, the U.S. Cybersecurity and Infrastructure Security Agency (CISA) issued a directive to all federal agencies to urgently patch a critical remote code execution (RCE) vulnerability (CVE-2025-8110) in Gogs, a popular open-source git service, following multiple waves of active zero-day exploitation. The flaw leveraged a path traversal issue via the PutContents API, allowing authenticated attackers to overwrite files outside repositories—including SSH command configurations—to gain arbitrary code execution. At least 700 internet-facing Gogs servers showed signs of compromise, implicating risks across the federal enterprise. This incident underscores the accelerated threat posed by zero-day exploits targeting software supply chain and collaboration tools exposed to the internet. The increase in attacks against widely used developer platforms, combined with slow patch adoption and the rapid weaponization of vulnerabilities, demands renewed attention to secure configuration, real-time monitoring, and timely security updates.

Low impact

Kill Chain

ICInitial Compromise(high)
PEPrivilege Escalation(high)
LMLateral Movement(medium)
C&CCommand & Control(medium)
EExfiltration(low)
IImpact(low)
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GoBruteforcer Botnet Exploits AI-Generated Weak Credentials to Breach Crypto Databases (2026)

GoBruteforcer Botnet Exploits AI-Generated Weak Credentials to Breach Crypto Databases (2026)

In January 2026, the GoBruteforcer botnet orchestrated a campaign targeting cryptocurrency and blockchain project databases. Attackers exploited weak or default credentials on exposed Linux-based services, including FTP, MySQL, PostgreSQL, and phpMyAdmin, to gain unauthorized access and deploy IRC bots and web shells. Many of the compromised credentials were traced to AI-generated server setup examples and outdated web stack configurations. Once inside, the botnet employed brute-force modules to propagate, staged payloads, and established redundant command-and-control channels. One notable tactic involved scanning TRON blockchain addresses for accounts with non-zero balances, signaling a financially motivated focus on blockchain assets. This incident highlights the evolving intersection of automated attack tools, AI-influenced misconfigurations, and crypto-driven targeting. The persistent exploitation of misconfigured infrastructure underscores rising risks to technology firms, especially as low-effort credential attacks increasingly leverage AI-generated default settings.

Medium impact

Kill Chain

ICInitial Compromise(high)
PEPrivilege Escalation(medium)
LMLateral Movement(medium)
C&CCommand & Control(medium)
EExfiltration(medium)
IImpact(medium)
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n8n npm Supply Chain Attack: OAuth Tokens Stolen via Malicious Community Nodes

n8n npm Supply Chain Attack: OAuth Tokens Stolen via Malicious Community Nodes

In early January 2026, threat actors targeted the n8n workflow automation ecosystem by publishing eight malicious npm packages that mimicked legitimate integrations. These packages prompted unsuspecting users to connect OAuth-protected services like Google Ads, Stripe, and Salesforce. Once installed as community nodes, the malware exfiltrated encrypted OAuth tokens from the n8n credential store by decrypting them with n8n's own master key and sending them to attacker-controlled servers. The campaign exploited developer trust in community packages and highlighted a dangerous new avenue for credential theft at scale. This incident reflects the increasing sophistication and frequency of supply chain attacks, particularly against workflow automation tools that centralize sensitive credentials. With open-source ecosystems growing rapidly, businesses face heightened urgency to scrutinize third-party integrations and adopt least-privilege, zero trust security practices.

Medium impact

Kill Chain

ICInitial Compromise(high)
PEPrivilege Escalation(medium)
LMLateral Movement(medium)
C&CCommand & Control(high)
EExfiltration(high)
IImpact(medium)
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Two Major Campaigns Expose AI/LLM Endpoint Security Flaws in 2024

Two Major Campaigns Expose AI/LLM Endpoint Security Flaws in 2024

In early 2024, security researchers observed two distinct attack campaigns targeting more than 91,000 public Large Language Model (LLM) endpoints. Threat actors systematically scanned for exposed LLM interfaces left accessible on the public internet, leveraging them to probe for sensitive data leaks and map organizational attack surfaces. Attackers exploited the unprotected AI endpoints primarily through direct web probes and API requests, taking advantage of lax access controls and lack of encryption. The business impact included the risk of sensitive internal data exposure, increased surface area for lateral movement, and potential regulatory non-compliance. The incident highlights the increasing threat to organizations deploying AI/GenAI technologies without robust security controls. As adoption of LLMs surges, attackers are pivoting to exploit these modern interfaces, driving urgency for enterprises to secure AI assets, enforce segmentation, and monitor for unauthorized use of LLM endpoints.

Medium impact

Kill Chain

ICInitial Compromise(high)
PEPrivilege Escalation(medium)
LMLateral Movement(medium)
C&CCommand & Control(medium)
EExfiltration(medium)
IImpact(medium)
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Researchers Uncover How Subtle Tuning Can Corrupt LLMs via Inductive Backdoors

Researchers Uncover How Subtle Tuning Can Corrupt LLMs via Inductive Backdoors

In January 2026, researchers published a pivotal study revealing new ways that adversaries can corrupt large language models (LLMs) through subtle data poisoning and finetuning techniques that exploit the models’ generalization abilities. The research demonstrated that minimal, targeted finetuning can induce LLMs to adopt outdated or harmful behaviors even outside the initial scope of manipulation. Notably, the study introduced the concept of "inductive backdoors," wherein LLMs generalize a malicious trigger and behavior relationship—resulting in broad, unpredictable misalignments and persona shifts not directly present in the source training data. No direct attacker, but the techniques expose exploitable weaknesses in LLM training pipelines and data supply chain security. This finding is urgent for organizations integrating AI/ML into business operations. It spotlights a new class of supply chain and insider risk: even small, unnoticed changes in model inputs or fine-tuning datasets can profoundly undermine trust, safety, and regulatory compliance in deployed AI systems.

High impact

Kill Chain

ICInitial Compromise(high)
PEPrivilege Escalation(medium)
LMLateral Movement(medium)
C&CCommand & Control(medium)
EExfiltration(medium)
IImpact(high)
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CISA Closes Era of Emergency Directives — Centralizes Federal Vulnerability Management in 2026

CISA Closes Era of Emergency Directives — Centralizes Federal Vulnerability Management in 2026

In January 2026, the U.S. Cybersecurity and Infrastructure Security Agency (CISA) retired ten Emergency Directives (EDs) that had been issued between 2019 and 2024 to mitigate high-risk vulnerabilities including DNS tampering, Microsoft Exchange flaws, Print Spooler vulnerabilities, SolarWinds compromise, and other widely exploited threats. CISA's review determined that remediation was complete and these urgent directives are now covered under Binding Operational Directive 22-01—which requires agencies to rapidly patch known exploited vulnerabilities (KEVs) in accordance with stricter deadlines. This mass retirement signals a shift from fragmented, incident-driven orders to centralized, ongoing vulnerability management via the KEV catalog. This move is especially relevant as threat actors continue to exploit unpatched vulnerabilities with increasing speed and sophistication. CISA’s new guidance streamlines federal agencies’ response, setting an industry precedent for proactive vulnerability management and rapid patch cycles aligned with emerging regulatory pressure and rising adversary activity.

Medium impact

Kill Chain

ICInitial Compromise(high)
PEPrivilege Escalation(medium)
LMLateral Movement(medium)
C&CCommand & Control(medium)
EExfiltration(medium)
IImpact(medium)
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Hackers Exploit Misconfigured Proxies to Access Paid LLM Services in 2026

Hackers Exploit Misconfigured Proxies to Access Paid LLM Services in 2026

In late 2025 and early 2026, threat actors launched coordinated campaigns to identify and exploit misconfigured proxy servers providing unauthorized access to commercial large language model (LLM) services. Using enumeration techniques and server-side request forgery (SSRF) vulnerabilities, attackers probed over 73 LLM endpoints—like OpenAI, Anthropic, and Google Gemini—producing more than 80,000 sessions. Their tactics included low-noise queries to bypass security alerts, the injection of malicious registry URLs, and Twilio SMS webhooks. While the activity appeared research-oriented at times, the scale and automated reconnaissance efforts were indicative of broader malicious reconnaissance likely intended for future exploitation or abuse of these valuable AI assets. This incident underscores a broader rise in cloud misconfiguration attacks and highlights escalating threats targeting AI infrastructure. As reliance on LLM APIs grows, so too does the risk of credential abuse and exploitation, placing new urgency on proactive cloud security, real-time monitoring, and zero trust principles across managed AI services.

Medium impact

Kill Chain

ICInitial Compromise(high)
PEPrivilege Escalation(medium)
LMLateral Movement(medium)
C&CCommand & Control(high)
EExfiltration(low)
IImpact(medium)
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