An India-aligned advanced persistent threat group known as Dropping Elephant has launched sophisticated cyberattacks against Pakistan’s defense sector using a newly developed Python-based backdoor delivered through an MSBuild dropper. The campaign demonstrates significant evolution in the threat actor’s tactics, techniques, and procedures, combining living-off-the-land binaries with custom malware to evade detection and establish persistent access […]
The ToddyCat APT group has developed new ways to access corporate email communications at target organizations.
Email remains the main way companies handle business communications, whether through their own servers like Microsoft Exchange or through cloud services such as Microsoft 365 and Gmail.
Many believe that cloud services provide better protection for company communications. Even when attackers break into a company’s network, email data stays in the cloud and appears safe.
However, the ToddyCat group has found ways around this assumption.
The group has evolved its methods to secretly access internal employee communications at targeted companies. Recent attacks took place during the second half of 2024 and early 2025.
These operations show how the attackers moved from traditional methods to new approaches that help them avoid detection.
Their latest technique uses a user’s browser to steal tokens for the OAuth 2.0 system, which then allows access to corporate email from outside the breached network.
Securelist security researchers identified these new attack methods and documented how ToddyCat changed its approach over time.
The group created tools that work quietly in the background, stealing authentication information and email data without triggering many security alerts.
The researchers found that ToddyCat has been constantly testing and improving its techniques to stay ahead of security teams.
Browser Data Theft Through Network Connections
The group updated its TomBerBil tool with a PowerShell version that works differently from earlier models. This new version runs on domain controllers with high-level access and reaches out to browser files across the network using the SMB protocol.
The tool collects data from Chrome, Edge, and Firefox browsers. It starts by reading a list of computer names from a file and then connects to each one through network shares.
Scheme of using the TCSectorCopy and XstReader tools (Source – Securelist)
The script creates folders to organize the stolen data and copies important browser files including Login Data, which stores saved passwords, Local State with encryption keys, Cookies files, and browsing History.
For Firefox, it grabs similar files like key3.db, signons.sqlite, key4.db, and logins.json from user profile folders. The tool also copies DPAPI encryption keys that Windows uses to protect user data.
With these stolen keys and user information, attackers can decrypt all the browser data on their own systems. The SMB protocol connections make the theft harder to spot because network file access appears normal in many environments.
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This week saw a lot of new cyber trouble. Hackers hit Fortinet and Chrome with new 0-day bugs. They also broke into supply chains and SaaS tools. Many hid inside trusted apps, browser alerts, and software updates.
Big firms like Microsoft, Salesforce, and Google had to react fast — stopping DDoS attacks, blocking bad links, and fixing live flaws. Reports also showed how fast fake news, AI
In October 2025, a significant breach exposed internal operational documents from APT35, also known as Charming Kitten, revealing that the Iranian state-sponsored group operates as a bureaucratized, quota-driven cyber-espionage unit with hierarchical command structures, performance metrics, and specialized attack teams. The leaked materials provide an unprecedented window into how this Islamic Revolutionary Guard Corps Intelligence […]
NVIDIA has released security updates addressing two critical code injection vulnerabilities in its Isaac-GR00T robotics software platform. The flaws could allow attackers with local system access to execute arbitrary code, escalate privileges, and tamper with sensitive data, potentially compromising robotic systems and their underlying infrastructure. The vulnerabilities, tracked as CVE-2025-33183 and CVE-2025-33184, affect all versions […]
A massive supply chain attack targeting the NPM accounts of automation giant Zapier and the Ethereum Name Service (ENS).
Identified by Aikido Security, the campaign is being orchestrated by the same threat actors responsible for the “Shai Hulud” self-propagating worm that first surfaced in September.
This latest wave, self-titled “Shai Hulud: The Second Coming,” has compromised multiple core packages and created over 19,000 public repositories containing stolen credentials.
The threat actor behind this campaign has pivoted from previous targets to inject malicious code directly into widely used dependencies within the Zapier and ENS ecosystems.
Unlike typical static malware, this attack uses a self-propagating worm that can rapidly expand. Once a developer installs an infected package, the malware activates to harvest sensitive secrets, including NPM tokens, GitHub Personal Access Tokens (PATs), and cloud infrastructure keys.
These stolen credentials are then immediately utilized to spread the infection further, creating a cascading effect across the open-source community. The speed of this propagation is alarming, with the impact surpassing the actor’s initial September campaign within just five hours of detection.
Data Exfiltration Tactics
The primary objective of this attack appears to be maximum disruption and data exposure. The malware employs TruffleHog, a tool designed to hunt for secrets, to exfiltrate sensitive data from infected environments.
The attackers are not just keeping these credentials to themselves. They are also sharing them publicly on GitHub in repositories with descriptive titles “Shai Hulud: The Second Coming.”
This public exposure exponentially increases the risk, as it allows other opportunistic threat actors to weaponize the exposed keys before organizations can rotate them, Aikido Security said to Cybersecurity News.
The sheer volume of created repositories suggests a highly automated execution meant to overwhelm security teams and incident responders.
The following packages have been confirmed as compromised and should be considered actively malicious.
Ecosystem
Package Name
Status
Zapier
zapier-platform-core
Infected / Malicious
Zapier
zapier-platform-cli
Infected / Malicious
Zapier
zapier-platform-schema
Infected / Malicious
Zapier
@zapier/secret-scrubber
Infected / Malicious
ENS
@ensdomains/ens-validation
Infected / Malicious
ENS
@ensdomains/content-hash
Infected / Malicious
ENS
ethereum-ens
Infected / Malicious
ENS
@ensdomains/react-ens-address
Infected / Malicious
ENS
@ensdomains/ens-contracts
Infected / Malicious
ENS
@ensdomains/ensjs
Infected / Malicious
ENS
@ensdomains/ens-archived-contracts
Infected / Malicious
ENS
@ensdomains/dnssecoraclejs
Infected / Malicious
Organizations utilizing any of the listed packages must assume a full compromise of their development environments. Security teams are urged to immediately rotate all GitHub, NPM, and cloud credentials to prevent unauthorized access.
It is critical to audit all dependencies and specifically scan GitHub organizations and employee accounts for repositories matching the “Shai Hulud” description.
To halt further spread, DevOps teams should temporarily disable NPM postinstall scripts in CI/CD pipelines where possible and enforce Multi-Factor Authentication (MFA) for all package maintainers.
Locking dependency versions and utilizing tools like SafeChain can help block the automatic execution of this malware while the ecosystem recovers.
Indicator Type
Value / Description
Repo Name Pattern
Shai Hulud: The Second Coming
Malware Behavior
Automated execution of TruffleHog for secret scanning
Zapier’s NPM account has been successfully compromised, leading to the injection of the Shai Hulud malware into 425 packages currently distributed across the npm ecosystem. The attack represents a significant supply chain threat, with the affected packages collectively generating approximately 132 million monthly downloads across critical infrastructure and development tools. The malware-laden packages span multiple […]
The Linux kernel development team has released version 6.18-rc7, marking another step toward the final 6.18 release expected next weekend. According to kernel maintainer Linus Torvalds, the release cycle remains on track despite a minor setback in the previous version that required immediate attention. What’s New in rc7 The release candidate includes a more modest […]
Cybersecurity researchers have uncovered a sophisticated Python-based malware that employs process injection techniques to hide inside legitimate Windows binaries.
This threat represents a new evolution in fileless attack strategies, combining multi-layer obfuscation with trusted system utilities to evade detection.
The malware’s ability to masquerade as harmless files while deploying a full Python runtime environment marks a significant advancement in delivery mechanisms that challenge traditional security approaches.
During a routine analysis at K7 Labs, security researchers identified this novel threat that uses a 65 MB blob containing mostly filler data with a small valid marshalled .pyc fragment hidden at the end.
This fragment contains the actual malicious code designed to inject processes into legitimate Windows executables.
The sample demonstrates several advanced features including multi-layer encoding, archive type masquerading, and bundling of a Python runtime with a signed executable name that appears legitimate to casual observation.
K7 Labs security analysts noted that the malware’s impact extends beyond initial infection, establishing persistent command-and-control communications that continue even after the original loader terminates.
The infection chain begins with a PE dropper that reconstructs a batch script through runtime decryption using SIMD operations.
This script drops config.bat into the public user directory, which then downloads a file disguised as a PNG image from cloud storage.
In reality, this PNG file is a RAR archive—a simple but effective trick that bypasses security filters treating image files as harmless.
The batch script extracts this archive using the built-in tar command, revealing three components: AsusMouseDriver.sys (a password-protected RAR disguised as a system file), Interput.json (renamed to Install.bat), and a legitimate WinRAR executable used for further extraction.
Execution Flow Chart (Source – K7 Labs)
Once executed, the Python interpreter processes command-line arguments “dcconsbot” and “dcaat” to trigger a sophisticated de-obfuscation chain through Base64 decoding, BZ2 decompression, Zlib decompression, and finally marshal loading to reconstruct the compiled Python bytecode in memory.
This code immediately targets cvtres.exe, a legitimate Microsoft resource conversion utility, for process injection.
Infection Mechanism Deep Dive
The core infection mechanism leverages a carefully orchestrated multi-stage extraction process that demonstrates the attackers’ deep understanding of Windows internals and security tool behaviors.
After the initial PE dropper executes, the config.bat script establishes C:\DragonAntivirus as a working directory before downloading the disguised archive.
The Install.bat script then renames the bundled WinRAR executable and uses it to extract the password-protected AsusMouseDriver.sys archive with a hardcoded password into C:\Users\Public\WindowsSecurityA.
This directory contains the fake ntoskrnl.exe (actually a bundled Python runtime) and the Lib\image blob containing the obfuscated payload.
Deobfuscated content (Source – K7 Labs)
A decoy PDF opens to distract users while malicious code executes silently, parsing the image file through the layered de-obfuscation routine before injecting into cvtres.exe and establishing encrypted C2 communications.
The malware’s ability to hide within legitimate Microsoft processes while maintaining encrypted communications channels makes it particularly dangerous for enterprise environments where traditional signature-based detection may fail to identify the threat.
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The rapid proliferation of large language models has transformed how organizations approach automation, coding, and research. Yet this technological advancement presents a double-edged sword: threat actors are increasingly exploring how to weaponize these tools for creating next-generation, autonomously operating malware. Recent research from Netskope Threat Labs reveals that GPT-3.5-Turbo and GPT-4 can be manipulated to […]