E mail safety has all the time been a cat-and-mouse sport. Viruses are invented, and antivirus software program is invented to catalog identified viruses and detect their presence in electronic mail attachments and URLs. As viruses morphed into extra subtle types of malware, cybersecurity instruments tailored to have the ability to scan for and detect these new threats. Phishing turned the following enviornment, giving start to new instruments in addition to an entire new class of protection often known as safety consciousness coaching. Now, the unhealthy guys are attacking AI agents to bypass present safety guardrails.
“AI assistants, copilots, and brokers considerably broaden 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 collection 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 electronic mail messages arrive at an inbox.
Conventional Strategy to E mail Safety
Most electronic mail safety instruments are designed to identify identified unhealthy alerts like suspicious hyperlinks, pretend domains that look actual, or attachments carrying malware. This strategy works effectively towards standard phishing, spam, and identified exploits. However cybercriminals are actually going after the various AI assistants and AI brokers which have turn into embedded within the office.
They do that by profiting from prompts (questions or instructions in textual content or code type) 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, resembling exfiltrating knowledge 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 Information Officer at Proofpoint, supplied an instance: The usual used for electronic mail messages often known as RFC-822 lays out using headers, plain textual content, and HTML. Not all of that is seen to a consumer. Attackers reap the benefits of this by embedding directions in messages which might be invisible to people however absolutely readable by an AI agent. When AI processes the textual content, the embedded directions are inadvertently executed. This could result in knowledge 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 Information Officer at Proofpoint.Proofpoint
“In latest assaults we’re seeing instances the place the HTML and plain textual content model are fully 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 may routinely act on an electronic 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 may assume twice about sending cash to a Nigerian checking account. An AI agent may 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 on daily basis, one third of the worldwide complete. As well as, it scans near 50 billion URLs and three billion attachments each day. That is accomplished inline i.e., whereas the e-mail is touring from the sender to the recipient.
“We’ve got positioned detection capabilities straight within the supply path, which suggests latency and effectivity are crucial,” stated Rapp.
This essential degree of pace is achieved by coaching smaller AI fashions particularly on detection, primarily based on examples and the foundational data of a big language mannequin (LLM). For instance, OpenAI’s GPT-5 is estimated to have as many as 635 billion parameters. Wading by that quantity of information for each electronic 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 achieve 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 means, 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 tons of of behavioral, reputational, and content-based alerts to get round assault vectors that may navigate their well beyond one technique.
AI Adjustments the Safety Recreation
AI brokers are being rolled out throughout the enterprise and client panorama. Sadly, the push to capitalize on AI’s potential typically relegates safety to an afterthought. The unhealthy guys know this. They’re AI-enabling their cybercrime strategies and applied sciences to good the artwork of phishing for the AI agent period.
“Safety tooling should evolve from detecting identified unhealthy indicators to deciphering intent for people, machines, and AI brokers,” stated Thiemann. “Approaches that establish malicious directions or manipulative prompts pre-delivery, ideally utilizing distilled AI fashions for low-latency inline safety, deal with a major hole in at the moment’s defenses.”
Proofpoint is forward of the pack with the position out of those capabilities. Count on different cybersecurity distributors to comply with go well with within the coming months. By that point, nevertheless, what different AI-borne menace will emerge?
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