Cybercrime Archives | Digital Watch Observatory

Deepfake attacks push organisations to rethink cybersecurity strategies

Organisations are strengthening their cybersecurity strategies as deepfake attacks become more convincing and easier to produce using generative AI.

Security experts alert that enterprises must move beyond basic detection tools and adopt layered security strategies to defend against the growing threat of deepfake attacks targeting communications and digital identity.

Many existing tools for identifying manipulated media are still imperfect. Digital forensics expert Hany Farid estimates that some systems used to detect deepfake attacks are only about 80 percent effective and often fail to explain how they determine whether an image, video, or audio recording is authentic. The lack of explainability also raises challenges for legal investigations and public verification of suspicious media.

Cybersecurity companies are creating new technologies to improve the detection of deepfake attacks by analysing slight signals that are difficult for humans to notice. Firms such as GetReal Security, Reality Defender, Deep Media, and Sensity AI examine lighting consistency, shadow angles, voice patterns, and facial movements. Environmental indicators such as device location, metadata, and IP information can also help security teams spot potential deepfake attacks.

However, experts say detection alone cannot fully protect organisations from deepfake attacks. Companies are increasingly conducting internal red-team exercises that simulate impersonation scenarios to expose weaknesses in verification procedures. Multi-factor authentication techniques can reduce the risk of employees responding to fraudulent communications.

Another emerging defence involves digital provenance systems designed to track the origin and modification history of digital content. Initiatives such as the Coalition for Content Provenance and Authenticity (C2PA) embed cryptographically signed metadata into media files, allowing organisations to verify whether content linked to suspected deepfake attacks has been altered.

Recent experiments highlight how testing these threats can be. In February, cybersecurity company Reality Defender conducted an exercise with NATO by introducing deepfake media into a simulated military scenario. The findings showed how easily even experienced officials can struggle to identify manipulated communications, reinforcing calls for automated systems capable to detecting deepfake attacks across critical infrastructure.

As generative AI tools continue to advance, organisations are expected to combine detection technologies, stronger verification procedures, and provenance tracking to reduce the risks posed by deepfake attacks.

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Hackers target WhatsApp and Signal in global encrypted messaging attacks

Foreign state-backed hackers are targeting accounts on WhatsApp and Signal used by government officials, diplomats, military personnel, and other high-value individuals, according to a security alert issued by the Portuguese Security Intelligence Service (SIS).

Portuguese authorities described the activity as part of a global cyber-espionage campaign aimed at gaining access to sensitive communications and extracting privileged information from Portugal and allied countries. The advisory did not identify the origin of the suspected attackers.

The warning follows similar alerts from other European intelligence agencies. Earlier this week, Dutch authorities reported that hackers linked to Russia were conducting a global campaign targeting the messaging accounts of officials, military personnel, and journalists.

Security agencies say the attackers are not exploiting vulnerabilities in the messaging platforms themselves. Both WhatsApp and Signal rely on end-to-end encryption designed to protect the content of messages from interception.

Instead, the campaign focuses on social engineering tactics that trick users into granting access to their accounts. According to the SIS report, attackers use phishing messages, malicious links, fake technical support requests, QR-code lures, and impersonation of trusted contacts.

The agency also warned that AI tools are increasingly being used to make such attacks more convincing. AI can help impersonate support staff, mimic familiar voices or identities, and conduct more realistic conversations through messages, phone calls, or video.

Once attackers gain access to an account, they may be able to read private messages, group chats, and shared files via WhatsApp and Signal. They can also impersonate the compromised user to launch additional phishing attacks targeting the victim’s contacts.

The alert echoes a previous warning issued by the Cybersecurity and Infrastructure Security Agency (CISA), which reported that encrypted messaging apps are increasingly being used as entry points for spyware and phishing campaigns targeting high-value individuals.

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BeatBanker malware targets Android users in Brazil

A new Android malware called BeatBanker is targeting users in Brazil through fake Starlink and government apps. The malware hijacks devices, steals banking credentials, tampers with cryptocurrency transactions, and secretly mines Monero.

Infection begins on phishing websites mimicking the Google Play Store or the ‘INSS Reembolso’ app. Users are tricked into installing trojanised APKs, which evade detection through memory-based decryption and by blocking analysis environments.

Fake update screens maintain persistence while silently downloading additional malicious payloads.

BeatBanker initially combined a banking trojan with a cryptocurrency miner. It uses accessibility permissions to monitor browsers and crypto apps, overlaying fake screens to redirect Tether and other crypto transfers.

A foreground service plays silent audio loops to prevent the device from shutting down, while Firebase Cloud Messaging enables remote control of infected devices.

The latest variant replaces the banking module with the BTMOB RAT, providing full control over devices. Capabilities include automatic permissions, background persistence, keylogging, GPS tracking, camera access, and screen-lock credential capture.

Kaspersky warns that BeatBanker demonstrates the growing sophistication of mobile threats and multi-layered malware campaigns.

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AI browsers expose new cybersecurity attack surfaces

Security researchers have demonstrated that agentic browsers, powered by AI, may introduce new cybersecurity vulnerabilities.

Experiments targeting the Comet AI browser, developed by Perplexity AI, showed that attackers could manipulate the system into executing phishing scams in only a few minutes.

The attack exploits the reasoning process used by AI agents when interacting with websites. These systems continuously explain their actions and observations, revealing internal signals that attackers can analyse to refine malicious strategies and bypass built-in safeguards.

Researchers showed that phishing pages can be iteratively trained using adversarial machine learning methods, such as Generative Adversarial Networks.

By observing how the AI browser responds to suspicious signals, attackers can optimise fraudulent pages until the system accepts them as legitimate.

The findings highlight a shift in the cybersecurity threat landscape. Instead of deceiving human users directly, attackers increasingly focus on manipulating the AI agents that perform online actions on behalf of users.

Security experts warn that prompt injection vulnerabilities remain a fundamental challenge for large language models and agentic systems.

Although new defensive techniques are being developed, researchers believe such weaknesses may remain difficult to eliminate.

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AI agents face growing prompt injection risks

AI developers are working on new defences against prompt-injection attacks that aim to manipulate AI agents. Security specialists warn that attackers are increasingly using social engineering techniques to influence AI systems that interact with online content.

Researchers say AI agents that browse the web or handle user tasks face growing risks from hidden instructions embedded in emails or websites. Experts in the US note that attackers often attempt to trick AI into revealing sensitive information.

Engineers are responding by designing systems that limit the impact of manipulation attempts. Developers in the US say AI tools must include safeguards preventing sensitive data from being transmitted without user approval.

Security teams are also introducing technologies that detect risky actions and prompt users for confirmation. Specialists argue that strong system design and user oversight will remain essential as AI agents gain more autonomy.

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Google outlines roadmap for safer generative AI for young users

Google has presented a strategy for developing generative AI systems designed to protect younger users better better while supporting learning and creativity.

The approach emphasises building conversational AI experiences that balance innovation with safeguards tailored to children and teenagers.

The company’s framework rests on three pillars: protecting young people online, respecting the role of families in digital environments and enabling youth to explore AI technologies responsibly.

According to Google, safety policies prohibit harmful content, including material linked to child exploitation, violent extremism and self-harm, while additional restrictions target age-inappropriate topics.

Safeguards are integrated throughout the AI development lifecycle, from user input to model responses. Systems use specialised classifiers to detect potentially harmful queries and prevent inappropriate outputs.

These protections are also applied to models such as Gemini, which incorporates defences against prompt manipulation and cyber misuse.

Beyond preventing harm, Google aims to support responsible AI adoption through educational initiatives.

Resources designed for families encourage discussions about responsible technology use, while tools such as Guided Learning in Gemini seek to help students explore complex topics through structured explanations and interactive learning support.

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AI-driven adaptive malware highlights new cyber threat landscape

Google’s cybersecurity division, Mandiant, has warned about the growing threat of AI-driven adaptive malware, highlighting how AI is reshaping the cyber threat landscape.

According to a recent report, adaptive malware can modify its behaviour and code in response to the environment it encounters, thereby evading traditional security tools. By analysing the security systems protecting a target, the malware can rewrite parts of its code to bypass detection.

Unlike traditional malware, which typically follows fixed instructions, adaptive malware can adjust its behaviour during an attack. This capability makes it more difficult for conventional cybersecurity tools to detect and block malicious activity.

Mandiant noted that such malware is increasingly associated with advanced persistent threat (APT) groups that conduct long-term, targeted cyber operations. These groups often pursue espionage objectives or financial gain while maintaining prolonged access to compromised systems.

AI is also being used to automate elements of cyberattacks. Machine learning algorithms allow malicious software to anticipate defensive measures and adjust its behaviour in real time. In some cases, attackers are integrating AI into broader automated attack chains. AI-driven malware can gather information, adapt its strategy, and continue operating with minimal human intervention.

Security researchers say autonomous AI agents may be capable of managing multiple stages of an attack, including reconnaissance, exploitation, and persistence, while remaining undetected.

To address these evolving threats, Mandiant recommends that organisations strengthen their cybersecurity strategies by deploying advanced detection and response tools, including AI-based systems that can identify anomalous behaviour. As AI capabilities continue to develop, cybersecurity experts say understanding adaptive malware and automated attack techniques will be essential for organisations seeking to protect their systems and data.

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AI and quantum computing reshape the global cybersecurity landscape

Cybersecurity risks are increasing as digital connectivity expands across governments, businesses and households.

According to Thales Group, a growing number of connected devices and digital services has significantly expanded the potential entry points for cyberattacks.

AI is reshaping the cybersecurity landscape by enabling attackers to identify vulnerabilities at unprecedented speed.

Security specialists increasingly describe the environment as a contest in which defensive systems must deploy AI to counter adversaries using similar technologies to exploit weaknesses in digital infrastructure.

Security concerns also extend beyond large institutions. Connected devices in homes, including smart cameras and speakers, often lack robust security protections, increasing exposure for individuals and networks.

Policymakers in Europe are responding through measures such as the Cyber Resilience Act, which will introduce mandatory security requirements for connected products sold in the EU.

Long-term risks are also emerging from advances in quantum computing.

Experts warn that powerful future machines could eventually break widely used encryption systems that currently protect communications, financial data and government networks, prompting organisations to adopt quantum-resistant security methods.

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EU explores AI image generation safeguards

The Council of the European Union is examining a compromise proposal that could introduce restrictions on certain AI systems capable of generating sensitive synthetic images.

The discussions form part of ongoing adjustments to the EU AI Act.

A proposed measure that would primarily address AI tools that generate illegal material, particularly content involving the exploitation of minors.

Policymakers are considering ways to prevent the development or deployment of systems that could produce such material while maintaining proportionate rules for legitimate AI applications.

Early indications suggest the proposal may not apply to images depicting people in standard clothing contexts, such as swimwear. The distinction reflects policymakers’ effort to define the scope of restrictions without imposing unnecessary limits on common image-generation uses.

The debate highlights broader regulatory challenges linked to generative AI technologies. European institutions are seeking to strengthen protections against harmful uses of AI while preserving space for innovation and lawful digital services.

Further negotiations among the EU institutions are expected as lawmakers continue refining how these provisions could fit within the broader European framework governing AI.

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Malicious npm package targets developers with Openclaw impersonation

Security researchers uncovered a malicious npm package impersonating an Openclaw AI installer, designed to infect developer machines with credential-stealing malware.

JFrog Security Research identified the attack in early March 2026 after the package appeared on the npm registry and was downloaded roughly 178 times.

The deceptive package mimics legitimate Openclaw tools and contains ordinary-looking JavaScript files and documentation. Hidden scripts run during installation, displaying a fake command-line interface and a fabricated system prompt that requests the user’s password.

Entering the password grants the malware elevated access and allows it to download an encrypted payload from a remote command server. Once installed, the payload deploys Ghostloader, a remote access trojan that persists on the system and communicates with attacker servers.

Researchers say the malware targets sensitive information, including saved passwords, browser cookies, SSH keys, and cryptocurrency wallet files. Developers are advised to remove the package immediately, rotate credentials, and install software only from verified sources.

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