Much of the state spending mirrors federal patterns. Daisychain again has the
highest overall spend, and OpenAI and Claude dominate among the general-purpose
AI vendors. DonorAtlas -- the AI-powered prospect research tool -- sticks out
for its usage in these states, sitting behind only Daisychain and OpenAI and
buoyed up by nearly $4,000 in spending by the California Democratic party.

Even though it has dominated so much media conversation, few candidates seem to
be reporting spending on AI tools designed specifically to create synthetic
audio and video, also known as ?deepfakes?. We found just six federal candidates
or committees reporting spending on the popular AI audio generator tool from
ElevenLabs, with total spending of about $1,400 led by independent candidate for
Colorado?s sixth congressional district Samir Witta. The AI image generator
service Midjourney has five reported federal campaign or committee users
reporting about $1,600, led by Sholdon Daniels, the Republican primary runner-up
in the Texas 30th district. Combined, those two firms had less than
$100 in reported spend across the four states.

However, recent data from the Wesleyan Media Project shows that at least 164
political ads in this cycle have included AI-generated media, supported by at
least $80m in ad spending. What this illustrates is that candidate and committee
disclosure reports are just the tip of the iceberg. They don?t cover spending on
AI by political consultants, media firms and other vendors hired by the
campaigns or by PACs, or independent committees raising and spending money aimed
at boosting candidates? campaigns. Those entities aren?t required to disclose
detailed expenditure reports, and are very likely where the bulk of campaign AI
usage is happening.

Since a large fraction of all spending in the campaign cycle will happen in the
final weeks leading to November, much remains to be seen about the totality of
how campaigns will leverage AI and what impact its use will have on voters?
decisions.

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Unidentified Flock Cameras in Florida

[2026.10.02] St. Lucie County in Florida discovered (alt link) a dozen Flock
cameras whose ownership it can?t identify, and that the county government had
not permitted.

I am reminded of the decade-old story of StingRay cell phone surveillance
devices in Washington, DC, whose operators were also unknown.

My guess is that in the StingRay case, the devices were operated by foreign
actors. This Flock case is more likely some local government entity that didn?t
bother getting approval. Were I a foreign actor, I would rather hack the
existing Flock network -- like Israel did with Tehran?s surveillance cameras --
than risk installing my own.

Regardless, once we normalize a surveillance infrastructure, both friends and
foes will take advantage of it.

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Another Historic Cipher Falls to AI

[2026.10.05] This one is from 1809, written by Napoleon?s nephew.

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Possible Vulnerability in Apple?s Automatic Reboot

[2026.10.06] 404Media is reporting (alternate link) that a cyber-weapons arms
manufacturer is exploiting a vulnerability in iOS to bypass its automatic reboot
security feature. This is the feature that automatically puts an iPhone into a
more secure state if it hasn?t been used for 72 hours.

The new technology to get around inactivity reboot was developed by Magnet
Forensics, the company behind GrayKey, a popular tool sold to law enforcement
agencies that allows them to unlock and access data stored in iPhones and
Android smartphones. Magnet has developed a new device called GrayKey Preserve
and a feature for its regular GrayKey devices called Evidence Preservation Mode,
according to the video.

?This is an absolute game changer for iOS forensics and a function that I wish
we had years ago,? a Magnet employee says in the leaked video, specifically
mentioning that the solution is targeted at the iPhone?s inactivity reboot
feature and the data it makes unavailable. GrayKey Preserve and Evidence
Preservation Mode are also designed to combat another iPhone feature that
automatically deletes certain data - such as cached locations, and recently
deleted photos and iMessages - after a certain number of days. ?We?re gonna be
able to preserve that data for an infinite amount of time.?

Presumably, now that Apple engineers know that this flaw exists they can find
and fix it. AI turns out to be really good at this sort of thing.

Another news article.

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Apple?s Verified Photography System

[2026.10.07] Apple just released a system called ?Reference Image.? It can
verify the image is exactly as taken by an iPhone -- new models only -- without
tying it to a specific iPhone or photographer. It can also verify that multiple
images came from the same iPhone.

Other industry solutions require a photographer or institution to vouch for an
image using their own credentials. We are concerned this puts some
photographers, such as those operating in conflict zones, in a difficult
position; it should not be necessary to forgo anonymity in order to prove image
authenticity. We built Apple Reference Image to avoid using an explicit, public
credential for photographers, and to avoid even implicit public association
between different photos taken by the same sensor. The final reference image is
instead signed by Apple?s signing service, after validation by PCC. That
signature is backed by Apple?s strongest technical guarantees.

Our implementation also protects the confidentiality of the image itself,
including from Apple. Merely capturing a reference image should never expose the
actual pixels to Apple or anyone else. We achieve this through the exceptional
privacy properties of PCC -- the nodes themselves are architected so that not
even Apple can access image data, just as Apple cannot see the information
processed for Apple Intelligence in PCC. While the revocation service must
maintain a private record of photo GUIDs and associated sensors to allow for
revocation, it never has access to the image data, and does not allow for public
access to this record. And as final revocation checks occur using on-device
lists, a device never reveals to anyone which photo it?s looking at in order to
find out whether it?s still valid.

The report makes for good reading; the details are interesting.

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How Technology Empowers -- and Imperils -- Dictators

[2026.10.08] This essay was written with Seva Gunitsky, and originally appeared
in Foreign Affairs.

Two weeks after Moscow?s full-scale invasion of Ukraine in March 2022, the
Russian TV Channel One editor Marina Ovsyannikova burst onto the set of the
evening newscast. She held up a hand-drawn sign behind the anchor?s head that
read: ?Stop the war. Don?t believe propaganda. They?re lying to you!? She
shouted, ?No to war!? until she was dragged away.

No one has protested the war on Russian television since then, partly as a
result of tighter security and a general climate of fear. But in October 2024,
Margarita Simonyan, one of Russia?s chief propagandists, gave another
explanation. A growing number of the RT network?s anchors, she explained to an
interviewer, are not real. ?That face doesn?t exist. We generated the voice and
everything else.? They were, she meant, produced by artificial intelligence. In
a follow-up interview with the newspaper Vedomosti, she spelled out the logic:
?These anchors don?t need a salary or insurance,? she said. ?They won?t get
arrested, and the police won?t search their homes. It?s all wonderful and
terrifying at the same time.?

This is AI?s promise to every autocratic ruler: the ability to maintain control
without delegating tasks to unreliable humans. It is an extremely attractive
prospect. No matter how powerful, dictators have always needed subordinates --
censors, propagandists, security guards, police officers, intelligence analysts,
and local bureaucrats -- to carry out their orders. But subordinates always pose
a potential threat. They could shirk, steal, lie, leak, or conspire against
their boss. As a result, one of the oldest dilemmas facing autocrats is how to
empower agents to carry out orders without also enabling them to turn against
their leader. Autocrats have usually managed the tradeoff by filling key
positions with mediocrities whose incapacity is, as the political theorist
Hannah Arendt put it, ?the best guarantee of their loyalty.? But this inevitably
makes it harder for dictatorships to govern and survive crises.

AI appears to offer autocrats two ways to resolve this long-standing dilemma.
First, it means they can now easily monitor and discipline their followers in
real time. A change in a local official?s spending habits or meeting schedules
can be flagged automatically by an AI system, without any need for
self-interested informants. Second, AI can eliminate underlings altogether. By
automating tasks that once required human discretion, rulers can replace
unreliable intermediaries with faithful algorithms that cannot be bribed or
manipulated. Officials in autocratic regimes have said as much. AI ?can
definitely replace half of officials,? Russia?s Digital Development Minister,
Maksut Shadaev, told a Moscow data forum in April 2025, adding, ?maybe slightly
more.?

Yet these promises of a self-running state are illusory, because AI is never
truly autonomous. Systems have to be built and maintained by a cadre of
engineers and data scientists whose expertise political leaders cannot evaluate.
The ruler who turns to AI to reduce a dependence on unreliable humans may end up
relying, more blindly than before, on the few AI specialists who keep the system
running. And this new digital Praetorian Guard may have the same weaknesses as
the old, which makes it a threat to the ruler.

Eyes and Ears

China is in the lead when it comes to developing AI systems that can monitor or
replace subordinates. Smart city programs in Beijing, Shanghai, and other urban
centers use AI to track performance and centralize oversight of local officials
who once operated in comfortable obscurity, subjecting them to an algorithmic
performance review. China also developed a ?Zero Trust AI system,? which it
deployed across roughly 30 counties and cities over the past decade. This system
cross-referenced more than 150 government databases to catch embezzlement and
nepotism by local officials. It worked a little too well, flagging 8,700
officials before local governments, under pressure from the bureaucrats it was
monitoring, began rolling it back. But Beijing has not gotten rid of its new
e-government portals, which use automated systems for issuing documents and
permits, reducing face-to-face interactions that bred petty corruption or
favoritism. The Chinese Communist Party, meanwhile, has plowed ahead with
researching what
it calls ?thought management,? or how to use AI to create microtargeted
propaganda. China?s army of Internet commentators, once composed of paid humans,
is already being replaced by bots.

Russia has been pursuing the same goals with a similar fervor. Moscow?s citywide
facial recognition system, deployed across 200,000 cameras, was used to identify
and apprehend protesters during the 2021 antigovernment demonstrations. The
central government has started using automated data collection and aggregation
to bypass regional officials who could taint the data or use it to promote their
own interests. In 2023, Russia?s Internet regulator launched Oculus, an AI
system that scans hundreds of thousands of images per day for prohibited
content, including political content -- orders of magnitude beyond what human
censors could process. The Russian security service?s Meliorator tool has been
used to create over a thousand profiles of fictitious Americans, primarily on X
(formerly Twitter), to spread Kremlin narratives at a fraction of the cost of
human troll farms.

Other autocracies are following in Beijing?s and Moscow?s footsteps. In April
2025, the United Arab Emirates created a Regulatory Intelligence Office that
uses AI to draft and amend federal laws, work once done by legislative staff. A
year later, UAE Prime Minister Sheikh Mohammed bin Rashid al-Maktoum announced
that autonomous AI agents would take over half of the federal government?s
operations within two years and that ?the performance of ministers, directors
general, and entities will be assessed based on their ability to adopt this
transformation.?

These innovations may reduce the number of bureaucrats autocrats need. But they
cannot actually create what dictators want most: a self-running state. Even
AI-generated television anchors need people to build and maintain them, and
censorship systems need people to retrain them as the vocabulary of dissent
shifts. Behind every AI model, there is a small group of engineers and data
scientists doing essential maintenance, and their work is so technical that
rulers cannot understand it.

This dependence thus becomes another form of power. The engineers who maintain
an autocrat?s surveillance apparatus, for example, can shape what the ruler
sees. They decide what information is important enough to pass along and in what
form to present it. They determine which threats get flagged, and they can
adjust the algorithms that select what content gets suppressed and who gets
arrested. And they can do this without anyone in the palace noticing. Autocrats
who turn to AI to escape a dependence on unreliable subordinates have only
transferred their vulnerabilities onto a new group of officials.

In fact, this new Praetorian Guard could be more dangerous than previous elites.
That is in part thanks to the opacity of AI technology but also because this
clique is much smaller. Roman emperors typically had tens of thousands of people
serving in the Praetorian Guard; modern autocrats rely on standing armies. But
with AI, autocrats will need only a small clique of engineers to build and
maintain large-scale AI systems. This might benefit rulers since they will have
fewer people to watch, yet it also concentrates points of failure, since a
devastating disruption requires only a handful of engineers and makes it easier
for members to scheme against the leader. The new guard?s members may also be
indispensable. A dictator can replace generals without destroying the army. But
running complex machine-learning systems requires such a specialized set of
skills that engineers can be difficult to replace without disruptions, giving
these actors great leverage.

The Indispensables

The importance of tech workers to autocracies has already become apparent. When
IT specialists began to flee Russia after the full-scale invasion of Ukraine in
February 2022, for example, the Kremlin responded not with threats but with
inducements, offering tech workers deferments from conscription. It exempted
their firms from taxes and subsidized their mortgages. When Russian President
Vladimir Putin ordered the mobilization of 300,000 men seven months later, IT
workers were granted full-on waivers. This might seem like overkill, given that
an AI system needs only a few engineers to run it. But a regime cannot know in
advance which engineers it will need, and it cannot train replacements quickly,
so it has to hold on to the entire talent pool from which these few are
selected.

These measures did not stem the outflow of roughly 100,000 specialists -- about
a tenth of Russia?s tech workforce -- over the course of 2022. But Moscow stuck
to bribery, because expertise is extremely difficult to conscript at gunpoint
and because conscripted experts might be less likely to do as instructed. Even
so, money and privilege cannot guarantee that these elites will stay loyal.
Autocrats should recall the lesson of the original Praetorian Guard: for a time,
it provided Roman emperors with protection and security. But then the
praetorians discovered their own indispensability, and by the second century,
they were auctioning off the empire to the highest bidder. This new set of
elites can do the same. In June 2023, when the column of Yevgeny Prigozhin?s
Wagner paramilitary company moved up the highway toward Moscow, Putin depended
on his security services to tell him what was happening. Future rulers in
Putin?s position will receive such warnings through machines: intercepted
communications sorted
by software, camera feeds filtered through recognition systems, regional reports
compiled into dashboards. The engineers who run those systems could strike a
deal with an upstart challenger and then drag their feet. They could delay the
data, let alerts arrive a few hours late, degrade feeds at inconvenient moments,
or make a recognition system stop functioning. In that scenario, the ruler would
be operating blind. The Praetorian Guard did not need to kill Emperor Nero to
replace him. It simply had to abandon him for a rival.

These programmers are unlikely to seize power for themselves, because they are
unlikely to carry what coup leaders ultimately require: guns. But there is
already precedent for engineers using their power to shape leadership
challenges. In 1991, when the Soviet army attempted to seize control from
Mikhail Gorbachev, a handful of programmers at the Relcom network kept
information flowing abroad and relayed Russian President Boris Yeltsin?s decrees
to audiences inside the country and abroad. The plotters could not stop the news
of Yeltsin?s defiance from spreading, and the coup collapsed within three days.

Slimming Down

AI will not let autocrats dismiss all their enforcers. Someone still has to make
arrests and run the prisons, and autocrats can buy loyalty by offering
supporters state jobs. But it will let authoritarians downsize, and the number
of officials ultimately matters less than how the ruler oversees them. Keeping
track of scheming or incompetent subordinates has always been the autocrat?s
chief burden. AI could lighten it, letting rulers watch their officials more
closely without paying as much active attention.

In the near term, then, AI may greatly benefit autocracies. Despite the many
obstacles to deployment, the technology is already bringing autocratic regimes
the upsides of cheaper surveillance, smarter censorship, and fewer human
subordinates to fear and distrust. But for autocratic rulers, the temptations of
artificial intelligence may re-create the same trap they are seeking to escape.
The more a regime depends on AI, the more it depends on the people who keep AI
running. And those people, like every other praetorian class in history, will
quickly discover what their indispensability is worth.

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FBI Arrests Suspect in FBI-Hacking Case

[2026.10.12] In September, hackers from a group called ShinyHunters announced
that they stole a trove of FBI data about its own agents. It was an intelligence
disaster.

Last week, the FBI arrested (alternate link) someone associated with that crime.

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Cyberattack on Connected Fridges in France

[2026.10.14] Another IoT cyberattack, this one in France:

Hackers gained control of the software that regulates the temperatures of the
refrigeration units, forcing some to warm to 50C (120F) overnight, according to
one supermarket chain affected.

[...]

Normally, supermarket freezers go through a short period of defrosting
overnight, in which temperatures rise slightly. But the hackers ordered the
units to heat up and stay hot, although Danfoss did not confirm any reports
about just how warm the fridges and freezers could become in that process.

Danfoss said the affected cold units were older models whose security software
could not be updated to ward off a risk they had identified.

Any IoT device that can?t be updated is vulnerable. And, probably, any IoT
device that can be updated is also vulnerable.

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The Future of AI Cryptanalysis

[2026.10.14] Matthew Green has been writing a rather pessimistic series of posts
about the potential for AI systems to vastly outperform humans in cryptanalysis
of both symmetric and public-key ciphers.

I am more optimistic than he is. That is, I have stronger faith in the
over-engineering cryptographers tend to do. I am trying to write this up in more
detail.

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Upcoming Speaking Engagements

[2026.10.14] This is a current list of where and when I am scheduled to speak:

I?m speaking at ATTENTION: Democracy, Rebuilt in Montreal, Quebec, Canada. The
event runs October 21-23, 2026, and my talk is on Wednesday, October 21. I?m
speaking at the University of Toronto in Toronto, Ontario, Canada, at 5 PM ET on
October 22, 2026.
I?m speaking at [un]prompted in San Francisco, California. The event runs
October 27-29, 2026, and my talk is at 11:35 AM PT on Thursday, October 29. I?m
speaking at the Catalyst Summit in Brampton, Ontario, Canada, on Wednesday,
November 18, 2026.
I?m speaking at QT Qonference 2026 in Toronto, Ontario, Canada, on Thursday,
November 19, 2026.
The list is maintained on this page.

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Since 1998, CRYPTO-GRAM has been a free monthly newsletter providing summaries,
analyses, insights, and commentaries on security technology. To subscribe, or to
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Bruce Schneier is an internationally renowned security technologist, called a
security guru by the Economist. He is the author of over one dozen books --
including his latest, Rewiring Democracy -- as well as hundreds of articles,
essays, and academic papers. His newsletter and blog are read by over 250,000
people. Schneier is a fellow at the Berkman Klein Center for Internet & Society
at Harvard University; a Lecturer in Public Policy at the Harvard Kennedy School
and the Munk School at the University of Toronto; a board member of the
Electronic Frontier Foundation, AccessNow, and the Tor Project; and an Advisory
Board Member of the Electronic Privacy Information Center and
VerifiedVoting.org. He is the Chief of Security Architecture at Inrupt, Inc.

Copyright ? 2026 by Bruce Schneier.

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