#FactCheck-AI-Generated Viral Image of US President Joe Biden Wearing a Military Uniform
Executive Summary:
A circulating picture which is said to be of United States President Joe Biden wearing military uniform during a meeting with military officials has been found out to be AI-generated. This viral image however falsely claims to show President Biden authorizing US military action in the Middle East. The Cyberpeace Research Team has identified that the photo is generated by generative AI and not real. Multiple visual discrepancies in the picture mark it as a product of AI.
Claims:
A viral image claiming to be US President Joe Biden wearing a military outfit during a meeting with military officials has been created using artificial intelligence. This picture is being shared on social media with the false claim that it is of President Biden convening to authorize the use of the US military in the Middle East.
Similar Post:
Fact Check:
CyberPeace Research Team discovered that the photo of US President Joe Biden in a military uniform at a meeting with military officials was made using generative-AI and is not authentic. There are some obvious visual differences that plainly suggest this is an AI-generated shot.
Firstly, the eyes of US President Joe Biden are full black, secondly the military officials face is blended, thirdly the phone is standing without any support.
We then put the image in Image AI Detection tool
The tool predicted 4% human and 96% AI, Which tells that it’s a deep fake content.
Let’s do it with another tool named Hive Detector.
Hive Detector predicted to be as 100% AI Detected, Which likely to be a Deep Fake Content.
Conclusion:
Thus, the growth of AI-produced content is a challenge in determining fact from fiction, particularly in the sphere of social media. In the case of the fake photo supposedly showing President Joe Biden, the need for critical thinking and verification of information online is emphasized. With technology constantly evolving, it is of great importance that people be watchful and use verified sources to fight the spread of disinformation. Furthermore, initiatives to make people aware of the existence and impact of AI-produced content should be undertaken in order to promote a more aware and digitally literate society.
- Claim: A circulating picture which is said to be of United States President Joe Biden wearing military uniform during a meeting with military officials
- Claimed on: X
- Fact Check: Fake
Related Blogs
Introduction
Agentic AI systems are autonomous systems that can plan, make decisions, and take actions by interacting with external tools and environments. But they shift the nature of risk by blurring the lines among input, decision, and execution. A conventional model generates an output and stops. An agent takes input, makes plans, invokes tools, updates its state and repeats the cycle. This creates a system where decisions are continuously revised through interaction with external tools and environments, rather than being fixed at the point of input.
This means the attack surface expands in size and becomes more dynamic. Instead of remaining confined to components as in traditional computational systems, they spread in layers and can continue to grow through time. To understand this shift, the system can be analysed through functional layers such as inputs, memory, reasoning, and execution, while recognising that risk does not remain isolated within these layers but emerges through their interaction.
Agentic AI Attack Surface
A layered view of how risks emerge across input, memory, reasoning, execution, and system integration, including feedback loops and cross-system dependencies that amplify vulnerabilities.
Input Layer: Where Untrusted Data Becomes Control
The entry point of an agent is no longer one prompt. The documents, APIs, files, system logs and the outputs of other agents can now be considered input. This diversity is significant due to the fact that every source of input carries its own trust assumptions, and in the majority of cases, they are weak.
The most obvious threat is prompt injection, where inputs are treated as instructions rather than data. Since inputs are treated as instructions, a virus, a malicious webpage, or a document can contain instructions that override system goals without necessarily being detected as something harmful.
Indirect prompt injection extends this risk beyond direct user interaction. Instead of targeting the interface, attackers compromise the retrieval process by embedding malicious instructions within external data sources. When the agent retrieves and processes the data, it treats the embedded content as legitimate input. As a result, the attack is executed through normal reasoning processes, allowing the system to act on untrusted data without recognising the manipulation.
Data poisoning also occurs at runtime. In contrast to classical poisoning (where training data is manipulated), runtime poisoning distorts the agent’s perception of its environment as it runs. This can change decisions without causing apparent failures.
Obfuscation introduces another indirect attacker vector. Encoded instructions or complicated forms may bypass human review but remain readable to the model. This creates asymmetry whereby the system knows more about the attack than those operating it. Once compromised at this layer, the agent implements compromised instructions which affect downstream operations.
Context and Memory: Persistence of Influence
Agentic systems depend on memory to operate efficiently. They often retain context across sessions and frequently store information between sessions.
This introduces a different type of risk: persistence. Through memory poisoning, attackers can insert false or adversarial information into sorted context, which then influences future decisions. Unlike prompt injection, which is often limited to a single interaction, this effect carries forward. Over time, the agent begins to operate on a distorted internal state, shaping decisions in ways that may not be immediately visible.
Another issue is cross-session leakage. Information in a particular context may be replayed in a different context when memory is being shared or there is insufficient memory separation. This is specifically dangerous in those systems that combine retrieval and long-term storage. The context management in itself becomes a weakness. Agents are required to make decisions on what to retain and what to discard. This is susceptible to attackers who can flood the context or manipulate what is still visible and indirectly affect reasoning.
The underlying problem is structural. Memory turns data into a state. Once state is corrupted, the system cannot easily distinguish valid knowledge from adversarial influence.
The issue is structural. Memory converts temporary data into a persistent state. Once this state is weakened, the system cannot reliably separate valid information from adversarial influence, making recovery significantly more difficult.
Reasoning and Planning: Manipulating Intent Without Breaking Logic
The reasoning layer is where agentic AI stands apart from traditional systems. The model no longer reacts to inputs alone. It actively breaks down objectives, analyses alternatives, and ranks actions.
At the reasoning stage, the nature of risk shifts. The concern is no longer limited to injecting instructions, but to influencing how decisions are made. One example is goal manipulation, where the agent subtly reinterprets its objective and produces outcomes that are technically correct but strategically harmful. Reasoning hijacking operates within intermediate steps, altering how constraints are evaluated or how trade-offs are prioritised. The system may remain internally consistent, which makes such deviations difficult to detect.
Tool selection becomes a critical control point. Agents decide which tools to use and when, so influencing these choices can redirect execution without directly accessing the tools themselves. Hallucinations also take on a different role here. In static systems, they remain errors. In agentic systems, they can trigger actions. A perceived need or incorrect judgement can translate into real-world consequences.
This layer introduces probabilistic failure. The system is not fully weakened, but it is nudged towards decisions that appear reasonable yet are incorrect. The risk lies in how those decisions are justified.
Tool and Execution: When Decisions Gain Reach
Once an agent begins interacting with tools, its behaviour extends beyond the model into external systems. APIs, databases, and services become part of the execution path.
One key risk is the use of unauthorised tools. When agents operate with broad permissions, any manipulation of the upstream can be converted into real-world actions. This makes access control a central security concern. Command injection also takes a different form here. The agent generates commands based on its reasoning, so if that reasoning is compromised, the resulting actions may still appear valid despite being harmful.
External tool outputs introduce another risk. If these systems return corrupted or misleading data, the agent may accept it without verification and incorporate it into its decisions. It is also becoming increasingly reliant on third-part tools and plugins adds to this exposure. If these components are compromised, they can affect behaviour without directly attacking the core system, creating a supply-side risk.
At this stage, the agent effectively operates as an insider. It holds legitimate credentials and interacts with systems in expected ways, making misuse harder to identify.
Application and Integration: System-Level Exposure
Agentic systems rarely operate in isolation. They are embedded in larger environments, interacting with identity systems, business logic, and operational workflows.
Access control becomes a major vulnerability. Agents tend to operate across multiple systems with various permission models, creating irregularities that can be exploited. Risks also arise from identity and delegation. In case an agent is operating on behalf of a user, then any vulnerabilities in authentication or session management can allow attackers to assume that authority.
Workflow execution amplifies these risks. Agents can initiate multi-step processes such as transactions, updates, or approvals. Manipulating a single step can change the result of the entire workflow. As integrations increase, so do the number of interaction points, making cumulative risk harder to track.
At this layer, failures are not isolated. They propagate into business operations, making consequences harder to contain.
Output and Action: Where Failures Become Visible
The output layer is where failures become visible, though they rarely originate there.
Data leakage has been a key concern. Agents may disclose information they are allowed to access, especially when tasks boundaries are not clearly defined. Misinformation and unsafe outputs are also important, particularly when outputs directly influence actions or decisions.
Generated code and commands introduce execution risk. If outputs are used without validation, errors or manipulations can have system-level effects. The shift towards autonomous action increases this risk, as small upstream deviations can lead to significant consequences without human intervention. This layer reflects symptoms rather than root causes. Addressing it alone does not reduce the underlying risk.
Beyond Layers: The Missing Dimension
A layered view helps, but it does not capture the full picture. Agentic systems are defined by continuous interaction across layers.
The key missing dimension is the runtime loop. Inputs shape reasoning, reasoning drives action, and actions feed back into both reasoning and memory. These cycles create feedback loops, where small manipulations may escalate over time. This also reduces observability. With multiple interacting components, it becomes difficult to trace cause and effect or identify where failures originate.
Supply chain dependencies add another layer of risk. Models, datasets, APIs, and plugins each introduce their own points of failure. A compromise at any of these points can propagate across the system. The attack surface also includes governance. Weak supervision, unclear responsibility, or excessive autonomy increase overall risk. Human control is not external to the system; it is part of its security.
Conclusion: Structuring the Attack Surface
Agentic AI expands the attack surface beyond traditional systems. It is both recursive and stateful. Risk does not just accumulate across layers; it moves and changes as the system operates.
Any useful representation must go beyond a linear stack. It should capture feedback loops, persistent state, and cross-layer dependencies that characterise the way these systems actually behave. The system is not a pipeline but a cycle. That is where both its capability and its risk emerge.
Introduction
The Chairman of Vardhman Group, Mr SP Oswal, an India-based textile manufacturer, fell victim to a cyber fraud scheme that cost him ₹7 crore. The scam unfolded on August 28 and 29, conning Mr Oswal into transferring Rs 7 crore into multiple bank accounts. As per the recent reports, the Police have managed to freeze these accounts and recover over Rs 5 crore as of now. The fraudsters convinced Mr SP Oswal that he was a suspect in a money laundering investigation and held on a “Digital Arrest”. These are sophisticated cyber frauds where cyber-criminals impersonate law enforcement officials or other authorities and target innocent individuals with manipulative tactics. The scam targets are often contacted out of the blue, on Instant messaging apps like WhatsApp and informed that their bank accounts, digital identities, or other online assets have been compromised. Criminals play into the victims' fear by threatening them with imminent arrest, legal consequences, or public humiliation if they don't cooperate with a series of urgent demands.
Posing as Officials, Fraudsters Orchestrate ₹7 Crore Scam
The investigation revealed that the fraudsters posed as members of the Central Bureau of Investigation (CBI). They had contacted Mr Oswal and claimed that his Aadhaar had been misused in a case involving fake passports and financial fraud. The imposter conducted a video call in a police uniform using a background with the CBI logo. The fraud escalated further, Mr Oswal got a fake "arrest warrant" on WhatsApp allegedly authorised by the Supreme Court. Fraudsters convinced Mr Oswal to transfer ₹7 crores to facilitate bail proceedings, claiming he was under "digital arrest". The meticulously planned scam involved fake documents, a virtual courtroom, and relentless intimidation tactics leaving Mr Oswal effectively under "digital arrest" for two days. While the police have successfully recovered over Rs 5 crore so far, this case highlights the alarming threat of digital impersonation of law enforcement authorities.
Legal Outlook on the Validity of Digital Arrests
In India, the main laws governing cyber crimes are the Information Technology Act, of 2000 and the rules made under therein, and the newly enacted Bhartiya Nyaya Sanhita, 2023. Recently enacted new criminal laws do not provide for any provision for law enforcement agencies conducting a digital arrest. The law only provides for service of the summons and the proceedings in an electronic mode. Hence, there are no provisions for conducting 'digital arrests' as per the laws of the country.
Further, It should be noted that the Indian Cyber Crime Coordination Centre (I4C), under the Ministry of Home Affairs, coordinates the activities related to combating cybercrime in the country. MHA works closely with other ministries to counter these frauds. The I4C also provides technical support to the police authorities of states/UTs for the identification and investigation of these cases.
Best Practices to Avoid Digital Arrest Scams
- To protect yourself from scams, it is crucial to verify the identity of individuals claiming to be law enforcement or government officials and use official contact channels to confirm their credentials.
- Be cautious of pressure tactics used by fraudsters, especially demands for quick payment over unverified communication platforms like WhatsApp.
- Cross-check official documents with legal advisors or relevant authorities.
- Never share sensitive personal information, such as your Aadhaar number, over phone calls, emails, or messages without verifying the request's authenticity.
- Avoid untraceable payments, such as cryptocurrency or prepaid cards, without validating the transaction's legitimacy, especially under duress.
- Stay informed on scam techniques, particularly those involving impersonation and digital threats.
- Enable Two-Factor Authentication (2FA) for sensitive online accounts to prevent misuse.
- Consult advice from legal professionals if you receive threatening communication involving digital arrest or legal actions and do not take any action on the asks of persons posing as legitimate authorities.
- In case of any cybercrime, you can file a complaint at cybercrime.gov.in or helpline number 1930. You can also seek assistance from the CyberPeace helpline at +91 9570000066.
Conclusion
The digital arrest of Vardhman Group's CEO underscores the increasing sophistication of cyber fraud schemes, which exploit fear and urgency, leading to severe financial and reputational harm. No one is immune from cybercrime, vigilance is essential at all leadership levels. While laws like the IT Act and initiatives taken by the I4C help combat cybercrime, rapidly evolving threats demand proactive safety measures. Beyond the possibility of financial loss, incidents like this jeopardise brand reputation, investor confidence, and operational stability. Be cautious of such threats and exercise due care and caution while navigating the digital landscape. Be aware of such kinds of scams and the manipulative tactics used by fraudsters to avoid them. By staying vigilant and aware we can avoid the growing scam of digital arrests.
References
- https://www.business-standard.com/companies/news/digital-arrest-and-rs-7-crore-heist-how-vardhman-group-head-was-tricked-124100100832_1.html
- https://www.hindustantimes.com/business/vardhman-group-chairman-sp-oswal-duped-of-rs-7-crore-fraudsters-posed-as-cbi-101727666912738.html
- https://www.msspalert.com/native/digital-arrests-the-new-frontier-of-cybercrime
Executive Summary
A video is being widely shared on social media with the claim that a terrorist attack took place at the ISKCON Temple in Patna. The posts claim that terrorists opened indiscriminate fire at security personnel deployed at the main gate, carried out bomb blasts, and took two priests hostage. CyberPeace Research Wing’s research found that the claim of a terrorist attack on the ISKCON Temple in Patna is false. The viral video is not from an actual attack but from a security mock drill conducted at the temple.
Claim
A Facebook post shared a video claiming: "Three suspected terrorists entered the ISKCON Temple! Security guards were shot at the gate. Three suspected terrorists carrying modern weapons and hand grenades suddenly entered the Patna ISKCON Temple in the morning and killed the security personnel deployed at the gate. They then carried out a bomb blast, creating panic inside the temple campus."
The Facebook post archive can be accessed here. Similar posts can be found here and here.
https://www.facebook.com/reel/2501959103601059
Factcheck
To verify the claim, we extracted keyframes from the viral video and conducted a reverse image search. During the search, we found reports from several credible media organisations clarifying that the video was not related to any real terrorist attack but was from a mock drill conducted to assess the preparedness of security forces. According to a Dainik Bhaskar report published on July 29, a security mock drill was conducted at the ISKCON Temple in Patna. During the exercise, a simulated emergency situation was created in which police personnel were assigned the role of suspected terrorists and were made to enter the temple premises. The drill involved personnel from Kotwali, Jakkanpur and Buddha Colony police stations, along with magistrates and around 50 police personnel who reached the spot and took charge of the situation. An ATS team was also immediately called during the exercise.
The report also quoted Patna ASP (Law and Order) Krishna Murari Prasad, who clarified that the exercise was organised to strengthen the temple’s security arrangements.
A Navbharat Times report published on July 29 also stated that, as part of the planned mock drill, three Bihar Police personnel carrying advanced weapons and hand grenades were sent inside the ISKCON Temple premises. Security agencies responded quickly, cordoned off the area, and the ATS team took control of the personnel and mock explosives, successfully completing the exercise.
During our research , we also found a post dated July 29, 2026, on the official Facebook page of the Home Department, Government of Bihar, regarding the mock drill.
The post stated that the Bihar ATS successfully conducted a security mock drill at the ISKCON Temple premises in Patna. The objective of the exercise was to test coordination between security agencies and stakeholders, quick response capabilities, and the effective implementation of Standard Operating Procedures (SOPs) during a possible terrorist attack or emergency situation. The post further mentioned that the drill included a rapid response to suspicious activity, area sanitisation, safe evacuation of devotees, search for suspects, and other necessary security measures.
https://www.facebook.com/HomeDeptBihar/posts/1492697179568423?ref=embed_post
Conclusion
The evidence gathered during the research confirms that the viral claim is false. The video being shared with the claim of a terrorist attack on Patna’s ISKCON Temple actually shows a security mock drill conducted by the authorities to assess emergency preparedness.
