Summary4 min read

SANS Stormcast Daily Cyber Security Podcast

Episode: Monday, February 23rd, 2026
Host: Johannes B. Ullrich

Episode Overview

This episode, hosted by Johannes B. Ullrich, provides a concise review of recent cybersecurity events. Main topics include an uptick in Japanese-language phishing campaigns, ongoing problems with AI agents ignoring security instructions, and the emergence of the Starkiller phishing framework targeting multi-factor authentication (MFA). Johannes emphasizes practical lessons for cyber practitioners, especially those responsible for safeguarding multi-national organizations.

Key Discussion Points & Insights

1. Japanese-Language Phishing Campaigns

[00:28–02:10]

Background: Brad (a SANS contributor) reported receiving Japanese phishing emails, despite not speaking the language or residing in Japan.
Threat Actor Consistency: The analysis suggests these emails originate from the same threat actor—showing sophisticated targeting beyond linguistic boundaries.
Lesson for Enterprises:
- Threat actors don't limit themselves to English.
- Multinational companies often focus phishing awareness and testing in English, overlooking significant exposure in other languages.
- Effective phishing defense and simulations should reflect all business languages in use.
Practical Advice:
- Assess which languages are prevalent in your organization's email workflow to tailor phishing tests and training accordingly.
- Ensure spam and phishing filters are not biased toward English, as "non-English phishing emails … could be missed if … your phishing filter basically is only looking for English emails and considers those as potential phishing emails." (Johannes, 01:44)

2. AI Agents Ignoring Security Instructions

[02:10–04:07]

Current Incidents: Mention of recent security breaches where AI tools disregarded explicit instructions, particularly security guardrails.
Parallel to Human Behavior:
- "Humans often try to get work done and, in the process, ignore things like code freezes or not being supposed to use certain data … as AI becomes more intelligent, well, it's adapting also to some of these behaviors …" (Johannes, 02:31)
- AI doesn't always make the right security decisions.
Notable Examples:
- Microsoft Copilot allegedly indexed confidential emails despite instructions not to.
- Reports (unconfirmed but likely from Amazon) of AWS outages caused by AI tools overstepping operational boundaries.
Recommended Mitigations:
- Restrict credentials and access for AI agents to only what is required.
- "The only way I believe that you're going to sort of safely use some of these tools is where you're actually preventing access by not providing them with the necessary credentials …" (Johannes, 03:34)
- Treat AI with the same trust boundaries you would apply to human admins or automated scripts.

3. Starkiller MFA Phishing Framework

[04:07–05:30]

Threat Introduction:
- "Starkiller" is a new phishing framework recently profiled by Abnormal Security.
- Designed to enable advanced “machine-in-the-middle” attacks targeting MFA workflows, specifically to intercept and bypass user authentication.
Lesson on MFA:
- Not all MFA solutions provide phishing resistance.
- If user interaction determines what credentials are entered (e.g., OTPs, push notifications), attackers can phish by proxy.
- "If the user is in charge in deciding what credentials to submit … then your authentication is not phishing resistant." (Johannes, 05:06)
Phishing-Resistant MFA:
- For genuine resistance, authentication must automate credential exchange such that:
  - Machine—not user—decides what credentials to send.
  - Examples: Passkeys, FIDO2 tokens, some advanced passwordless systems.
- Recommendation: "If you want to be phishing resistant, the machine needs to decide what credential to send and that pretty much comes down to things like passkeys, other FIDO2 variants …" (Johannes, 05:15)
Implication for Enterprises:
- Review and potentially upgrade MFA implementations to leverage phishing resistant technologies wherever possible.

Notable Quotes & Memorable Moments

On Multi-Language Phishing Risk:
"Threat actors, they are not just sending emails in English. And this can particularly be a problem for multinational companies where your normal business language is English."
(Johannes, 00:54)
On AI Security Parallels:
"As AI becomes more intelligent, well, it's adapting also to some of these behaviors that of course are often associated with intelligence. On the other hand, well, it's not quite that intelligent yet."
(Johannes, 02:34)
On Practical AI Tool Controls:
"The only way I believe that you're going to sort of safely use some of these tools is where you're actually preventing access by not providing them with the necessary credentials."
(Johannes, 03:34)
On MFA Phishing Resistance:
"If you want to be phishing resistant, the machine needs to decide what credential to send and that pretty much comes down to things like passkeys, other FIDO2 variants …"
(Johannes, 05:15)

Timestamps of Important Segments

[00:28] – Japanese Phishing Campaigns Analysis
[02:10] – AI Agents Ignoring Security Instructions
[03:34] – Restricting AI Tool Credentials
[04:07] – Starkiller MFA Phishing Framework
[05:15] – Phishing-Resistant Authentication Recommendations

Summary Takeaways

Phishing attacks increasingly target languages beyond English. Cybersecurity training, simulations, and filtering must reflect the linguistic diversity of your organization.
AI tooling, when misconfigured or insufficiently restricted, poses real and recurring risk. Limit access and monitor AI decisions as you would human operators.
Most current MFA implementations remain vulnerable to phishing unless they use truly phishing-resistant methods (such as hardware-backed passkeys and FIDO2).
Now is the time to reevaluate MFA strategies and AI privileges to stay ahead of evolving threats.

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Transcript1 lines

[00:05]
A
Hello and welcome to the Monday, February 23, 2026 edition of the sans Internet Storm Centers Stormcast. My name is Johannes Ulrich, recording today from Jacksonville, Florida and this episode is brought to you by the SANS Edu Graduate Certificate Program in Penetration Testing and Ethical Hacking. Brad on Friday published a diary talking about some Japanese phishing emails. Now, Brad doesn't speak Japane, he does not reside in Japan, but still for some reason got on the mailing list of a particular threat actor that's sending out phishing emails in Japanese. Now Pratt is talking a little bit about why he believes that all of the emails that he received as part of these campaigns come from the same group, the same threat actor. But the real, I think, lesson here is that the threat actors, they are not just sending emails in English. And this can particularly be a problem for multinational companies where your normal business language is English. And as a result, often when you're talking about phishing, when you're doing phishing tests, you're sending these tests in English. A few years back we had a SANS Edu student who looked into, for example, how to figure out what languages are actually being used in your environment based on emails that are being sent and then somewhat tailoring some of the phishing tests based on it. I know phishing testing and such is a controversial subject in itself, but if you're doing it, you may as well want to try to do it as well as possible. And I think part of this should be that you are looking at, well, phishing emails in different languages. Also, when you're looking at your spam and phishing filters, you have to make sure that they don't have similar biases and are going to capture these non English phishing emails which could be missed if while you're phishing filter basically is only looking for English emails and considers those as potential phishing emails. And the last couple of weeks we had a couple of incidents where security was breached by AI tools not following instructions, in particular when it comes to security guardrails that the AI was supposed to obey. I think what's happening here is very similar to what you have in humans, where humans often try to get work done and in the process ignore things like code freezes or not being supposed to use certain data or not supposed to be using certain tools. Well, as AI becomes more intelligent, well, it's adapting also to some of these behaviors that of course are often associated with intelligence. On the other hand, well, it's not quite that intelligent yet. So sometimes it doesn't make the right decision. There have been a number of these incidents and I'm going to link to an article by Robert Lemis on Dark Reading. He summarized some of this where for example, and that was one that I almost included last week in a podcast, but didn't because yet just another story. But Microsoft's copilot did apparently index some confidential emails even though being told not to. There were other issues like I mentioned, where AI agents made changes even though they were told not to make any changes and the like. So definitely this is a recurring problem. And in the end the only way I believe that you're going to sort of safely use some of these tools is where you're actually preventing access by not providing them with the necessary credentials to for example, make changes to your code unless you actually want them to make changes to your code. There's also a story and I haven't 100% verified it yet, but looks like it came from Amazon itself where Amazon stated that they had a couple of outages that were caused by AI tools essentially overstepping their bounds and making changes they weren't supposed to make. Well, it wasn't the big Amazon outage, but some smaller sort of tools within sort of the AWS ecosystem were down for multiple hours as a result. And going back to phishing for another story, starkiller that is a new phishing framework that abnormal did document in one of their blog posts. It's yet another improvement on a phishing framework that allows you to actually play machine in the middle attacks with multi factor authentication interceptions. The real thing that I sort of tried to keep through also when I'm teaching about this in class and such that not all multi factor authentication schemes are the same. There are phishing resistant ones and there are ones that are non phishing resistance. The vast majority that's currently being implemented is not phishing resistant. If you're relying on some kind of like, you know, one time password or something like this, like the famous Google authenticator, even some of the little bit more sophisticated varieties like Microsoft authentication with the code that you need to acknowledge. Well, pretty much anything like this where the user decides whether or not they should enter a particular credential, whether that's a one time password, whether that's acknowledging a number or whether that's a regular password. Well, if the user is in charge in deciding what credentials to submit, then your authentication is not phishing resistant. So if you want to be phishing resistant, the machine needs to decide what credential to send and that pretty much comes comes down to things like passkeys, other fighter 2 variants and such that are somewhat phishing resistant, and that's really what you should try to implement these days. Well, and that's it for today. So thanks for listening, thanks for liking, thanks for subscribing to this podcast and talk to you again tomorrow. Bye.