Electronic mail safety has all the time been a cat-and-mouse sport. Viruses are invented, and antivirus software program is invented to catalog recognized viruses and detect their presence in e mail attachments and URLs. As viruses morphed into extra refined types of malware, cybersecurity instruments tailored to have the ability to scan for and detect these new threats. Phishing turned the subsequent area, giving beginning to new instruments in addition to an entire new class of protection referred to as safety consciousness coaching. Now, the unhealthy guys are attacking AI agents to bypass present safety guardrails.
“AI assistants, copilots, and brokers considerably increase the enterprise assault floor in ways in which conventional safety architectures weren’t designed to deal with,” stated Todd Thiemann, a cybersecurity analyst at analysis agency Omdia.
Enter a sequence of AI-based options for Proofpoint Prime Threat Protection that had been launched on the firm’s Proofpoint Defend 2025 occasion in September. They thwart the efforts of hackers to subvert the actions of AI brokers by scanning for potential threats earlier than e mail messages arrive at an inbox.
Conventional Method to Electronic mail Safety
Most e mail safety instruments are designed to identify recognized unhealthy indicators like suspicious hyperlinks, pretend domains that look actual, or attachments carrying malware. This strategy works effectively towards typical phishing, spam, and recognized exploits. However cybercriminals at the moment are going after the numerous AI assistants and AI brokers which have turn out to be embedded within the office.
They do that by making the most of prompts (questions or instructions in textual content or code kind) that information AI models and AI brokers to both produce related responses or execute sure duties. More and more, emails carry hidden, malicious prompts that use invisible textual content or particular formatting designed to trick generative AI instruments like Microsoft Copilot and Google Gemini into taking unsafe actions, similar to exfiltrating information or bypassing safety checks.
“Immediate injections and different AI-targeted exploits characterize a brand new class of assaults that use text-based payloads that manipulate machine reasoning reasonably than human conduct,” stated Thiemann.
Daniel Rapp, Chief AI and Knowledge Officer at Proofpoint, supplied an instance: The usual used for e mail messages referred to as RFC-822 lays out the usage of headers, plain textual content, and HTML. Not all of that is seen to a consumer. Attackers benefit from this by embedding directions in messages which can be invisible to people however absolutely readable by an AI agent. When AI processes the textual content, the embedded directions are inadvertently executed. This will result in information being exfiltrated or system conduct being altered or corrupted. Legacy filters on the lookout for malware or malformed hyperlinks see nothing amiss.
Daniel Rapp, Chief AI and Knowledge Officer at Proofpoint.Proofpoint
“In current assaults we’re seeing circumstances the place the HTML and plain textual content model are utterly completely different,” stated Rapp. “The e-mail shopper renders the HTML model whereas invisible plain textual content accommodates a immediate injection that may be picked up and probably acted on by an AI system.”
There are two the reason why this technique is proving efficient: First, if an AI assistant has entry to an inbox, it could possibly robotically act on an e mail the moment it arrives. Second, Rapp stated the literal nature of AI brokers makes them vulnerable to phishing and different social engineering tips. A human would possibly assume twice about sending cash to a Nigerian checking account. An AI agent would possibly blindly perform a command to take action.
What differentiates the Proofpoint strategy is that the corporate scans emails earlier than they hit inboxes. It’s had loads of observe. The corporate scans 3.5 billion emails daily, one third of the worldwide whole. As well as, it scans near 50 billion URLs and three billion attachments every day. That is achieved inline i.e., whereas the e-mail is touring from the sender to the recipient.
“We’ve got positioned detection capabilities instantly within the supply path, which suggests latency and effectivity are crucial,” stated Rapp.
This obligatory degree of velocity is completed by coaching smaller AI fashions particularly on detection, based mostly on examples and the foundational information of a big language mannequin (LLM). For instance, OpenAI’s GPT-5 is estimated to have as many as 635 billion parameters. Wading by way of that quantity of information for each e mail isn’t possible. Proofpoint has fine-tuned its fashions all the way down to about 300 million parameters. It distills and compresses its fashions to realize low-latency, in-line efficiency with out sacrificing detection constancy. It additionally updates these fashions each 2.5 days to have the ability to successfully interpret the intent of the message itself, not simply scan for indicators. On this manner, it spots hid immediate injections, malicious directions, and different AI exploits earlier than supply.
“By stopping assaults pre-delivery, Proofpoint prevents consumer compromise and AI exploitation,” stated Rapp. “Our secure email gateway can see emails and stop threats before they hit the inbox.”
As well as, Proofpoint makes use of an ensemble detection structure. As a substitute of counting on a single detection mechanism, it combines lots of of behavioral, reputational, and content-based indicators to get round assault vectors which may navigate their well past one technique.
AI Adjustments the Safety Recreation
AI brokers are being rolled out throughout the enterprise and client panorama. Sadly, the frenzy to capitalize on AI’s potential usually relegates safety to an afterthought. The unhealthy guys know this. They’re AI-enabling their cybercrime methods and applied sciences to excellent the artwork of phishing for the AI agent period.
“Safety tooling should evolve from detecting recognized unhealthy indicators to decoding intent for people, machines, and AI brokers,” stated Thiemann. “Approaches that determine malicious directions or manipulative prompts pre-delivery, ideally utilizing distilled AI fashions for low-latency inline safety, deal with a major hole in in the present day’s defenses.”
Proofpoint is forward of the pack with the function out of those capabilities. Count on different cybersecurity distributors to comply with swimsuit within the coming months. By that point, nevertheless, what different AI-borne risk will emerge?
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