Identity-first security for Financial Services: Your best defense against AI credential sprawl

AI credential sprawl is the uncontrolled growth of login credentials across SaaS and AI-enabled tools, leading to tool sprawl, identity risk, and compliance gaps. To eliminate it, you must centralize credential management, enforce granular access controls, and prioritize identity-first security.

You already know AI adoption is reshaping work. And not just at your business. Employees at big brands like Amazon, Meta, and Microsoft are “tokenmaxxing” to hit usage targets, and the result is engineers spinning up apps at a fraction of the time it previously took. 

The result is a critical mass of duplicate tools no one’s tracking. Tool sprawl, however, is only the surface problem. 

Beneath it lies AI credential sprawl, one of the fastest growing identity risks. If you’ve seen the headlines, you know the danger isn’t theoretical. GitGuardian’s 2026 State of Secrets Sprawl report says there were 28.65 million hardcoded secrets in public GitHub commits in 2025. That’s a 34% year-over-year increase and the largest single-year jump ever recorded. 

And that’s not all, which isn’t surprising given the rate of AI adoption. The same report also says AI-assisted commits leak secrets at a rate of 3.2%compared to a 1.5% baseline for human-only GitHub commits. 

A commit is a saved snapshot of code changes in version history. AI can make commits faster, but it can also amplify your identity risks by making it easier to accidentally include secrets like API keys in the code. Based on the report, AI-assisted coding can more than double your credential exposure rate.

The good news is, by the end of this article, you’ll understand how AI credential sprawl is being exploited, and you’ll have a clear, practical framework for closing the gap, especially if you’re a small to mid-sized business.

But first, it helps to see what’s at stake when this problem goes unaddressed. 

Why is AI credential sprawl becoming the #1 identity risk in 2026?

AI credential sprawl is becoming the biggest identity risk because AI adoption has exploded the number of credentials, beyond what most teams can realistically track.

Every AI tool your team deploys is typically assigned credentials: API keys, SSH keys, OAuth tokens. Non-human identities (NHI) like AI agents rely on these credentials to authenticate and perform tasks on your behalf.

While cutting edge vault-based credentialing and token vault architecture have emerged as part of the first generation of agent-native credential systems, adoption is still early.  

The day-to-day reality is keys hardcoded in scripts, pasted into internal wikis, stored in plaintext JSON files, and embedded in knowledge bases agents ingest. All of which can be misused through prompt injection pathways.

At the core of these threats are the fact that large language models will generally read and execute instructions without concern for the provenance [origin] of the instructions themselves, meaning threat actors can embed malicious instructions into a variety of inputs with the goal of tricking AI models into executing their directions.

                                              Mike Kosak LastPass Director of Threat Intelligence

NHIs are also rarely tied to a single human owner and aren’t included in offboarding plans. So, secrets like API keys keep living, with broad permissions that can be potentially exploited.

In a survey of 5,000 IT and cybersecurity leaders across 17 countries, researchers found that:

• 70% of organizations have been affected by at least one identity-related breach in the past 12 months.

• Yet only 34.3% rotate and audit non-human identities (NHIs) weekly, while only 11.1% do so continuously.

AI is amplifying both sides of the problem

• Employees adopt AI faster = more non-human identities + credentials to track

• Attackers use AI = phishing attacks automated at scale

• The result = progressive rise in credential theft and identity risk

In March 2025, three Japanese teens (aged 14, 15, and 16) purchased illegally obtained credit card numbers and login credentials and used them to create fake mobile contracts at Rakuten Mobile. 

The teens managed to sell about 2,500 of these contracts, which earned them about 7.5 million yen in crypto revenue. 

In July 2025, a single attacker used Claude Code to draft extortion emails to target 17 organizations over the course of a month. And in December 2025, another attacker used Claude Code and ChatGPT to steal 195 million taxpayer records from the Mexican government. 

So, the barrier to fraud isn’t skill anymore. It’s credential access. 

And if your organization onboards AI tools without a clear picture of who has access to what, your identity risk escalates and the impact is business-critical: Data leakage, operational disruption, regulatory penalties, financial loss.

How does AI credential sprawl impact your business?

AI credential sprawl has direct, measurable cost to your operations, compliance standing, team productivity, and revenues.

1. Account takeover (ATO) at scale

According to the 2026 Verizon DBIR, nearly 40% of 2025 breaches had credential abuse in the attack chain. That’s a worrisome stat, but what’s changed for 2026 is the blast radius.

A compromised account that has an agent integration can approve invoices, reset passwords, change cloud settings, and authorize entire AI workflows. 

And if it has API access to financial systems, it can also drain balances or unwittingly serve as a mule account for cryptolaundering. 

While attackers hijack your AI-enabled tools to land a pay day, you face regulatory penalties, reputational damage, and revenue loss.

2. Compliance gaps that compound over time

Frameworks like SOX, the UK Corporate Governance Code, and the EU AI Act require strong 905976.   

In 2026, the challenge is proving that both human and non-human access touching critical systems are governed by policy and backed with the right controls – Security Boulevard

• In SOX environments, unmanaged SaaS and AI access can trigger a financial restatement, which is one of the most damaging outcomes because it signals a breakdown in internal controls.

• Under the UK Corporate Governance Code, the same failure can result in a negative audit opinion, which is a formal loss of trust in board oversight.

Protecting trust in operational controls is critical where AI access can impact operations and public confidence - KPMG

3. IT teams overwhelmed by access chaos

When AI agents are deployed, each with different levels of oversight, the result is tool and credential sprawl that’s difficult to secure, track, and maintain.

Over half of small to midsized organizations now employ AI agents daily, but fewer than 10% have governance in place. The inevitable outcome is access chaos.

4. Productivity friction for employees

Poor access governance doesn’t just create identity risk; it can also slow your team down. 

The average enterprise now manages 291 SaaS applications, up from 254 in 2023. 

And according to Deloitte’s 2026 State of AI report, the use of AI-enabled apps or agentic AI tools is expected to become nearly universal in the next two years, with 3 in 4 companies (74%) using it at least moderately and 23% using it extensively.

Yet, many teams still lack the necessary access governance controls for SOX-relevant apps. Instead, they’re compensating by storing credentials in Word docs, Excel spreadsheets, Slack messages, and Post-it notes.

These manual workarounds slow execution and introduce operational drag, which can ultimately manifest in security incidents. 

How do you recognize AI credential sprawl in your organization?  If any of these apply, you have an AI credential sprawl problem:  “We don’t know what SaaS or AI tools employees are using.”  “Some apps use SSO, but others don’t.”  “We handle access differently everywhere.”  “We rely on users to manage their own credentials.” Yet, traditional controls fail. Why? Most traditional IAM (identity & access management) tools were built to protect a single layer of access: passwords, tokens, or app-level permissions. But AI credential sprawl operates across all four layers at once: Tool sprawl: SaaS and AI app adoption happening faster than IT can inventory it Credential sprawl: passwords, API keys, and SSH keys multiplying across every new tool Token sprawl: OAuth and session tokens generated at login, rarely rotated or revoked Agent sprawl: AI agents operating on credentials no human is actively managing These layers don’t stack independently. They’re interconnected. Tool sprawl creates credential and token sprawl.  Without a purpose-built vault that issues ephemeral, scoped credentials for agents, every downstream permission the agent uses inherits the security posture of the human credential layer. So, if the human-level credential is broad and persistent, the agent inherits those weaknesses. LastPass secures that human credential layer. SaaS Monitoring identifies every SaaS and AI tool generating credential exposure before it falls off your radar. The vault centralizes passwords, API keys, and SSH keys, so they're not hardcoded in scripts or passed around in Slack. SaaS Protect controls who can authenticate to what across your app environment. Of course, agents should receive the narrowest scoped permissions for each task. But the human credential layer is the starting point because it determines how identities are scoped before agent privileges are granted.  In other words, securing the human credential layer first gives you a defensible starting point to secure everything else.  See which SaaS and AI tools your team is using right now, and which credentials are exposed. Get a 20-minute walkthrough with a LastPass specialist or 905976 to see your SaaS and AI risk exposure.

What’s the difference between AI agent sprawl and Shadow IT, and why does it matter?

Shadow IT depends on human actions. In contrast, an AI agent authenticates and acts on its own, pulling data and completing workflows autonomously.

That distinction matters because traditional controls were built for human-driven access. 

The starting point for controlling agent sprawl is knowing which AI tools are in use, who’s signing in to them, and whether those credentials are strong, unique, and managed. Centralized credential management with real-time SaaS and AI discovery gives you that foundation. 

Without it, you can’t meaningfully control downstream agent permissions, especially if your team isn’t yet ready for agent credential vaulting.

What ROI can I expect from addressing AI credential sprawl?

ROI shows up in three areas that matter if you’re a small to mid-sized team:

• Lower risk of a breach. A breach involving Shadow AI adds $670,000 to incident response costs. For a Professional Services firm, a single credential-based breach can cost both your client relationships and your business.

• Faster compliance audits. About 76% of shadow AI tools fail to meet SOC 2 compliance standards – SQ Magazine. When credentials are centralized, access is documented, and SaaS and AI usage is visible in real time, audit preparations shift from a tedious manual exercise to automated reporting before an audit.

• Better cyber insurance terms. Insurers are increasingly requiring documented evidence of MFA enforcement and access controls. If your team can demonstrate centralized credential hygiene and SaaS visibility, you’re better positioned to qualify for coverage, maintain it after a claim, and negotiate lower premiums.

How do leading organizations control credential sprawl effectively?

Organizations that control credential sprawl effectively tend to prioritizeaccess governance.

They focus on three (3) core priorities

1. SaaS and AI discovery: Real time visibility into every SaaS and AI tool in use
2. Centralized credential management system: Strong, unique passwords for every account, MFA enforcement across all users, and secure sharing that eliminates the need for credentials to live in email threads or shared docs.
3. Controlled access in the browser: Risky logins surfaced and user guidance provided at the moment of access 

AI credential sprawl is an access governance problem. Traditional password managers, IAM platforms, and CASBs have their place. But each solves only part of the equation. They provide no: Visibility into real-time login behavior  Insights into SaaS and AI tool usage  Controls across all credentials That’s why leading organizations are moving toward unified Secure Access solutions that combine:  Credential management  SaaS + AI discovery  Granular access controls + behavioral visibility See which AI tools your team is using right now, and which credentials are exposed. Get a 20-minute walkthrough with a LastPass specialist or start a free trial now to see your SaaS and AI risk exposure.

LastPass vs 1Password vs Dashlane vs Keeper Security for identity-first security

See how LastPass compares to other vendors in helping you manage access across your SaaS and AI ecosystem.

Ready to identify hidden AI credential sprawl and gain full visibility into your SaaS and AI access? Book your 20-minute demo now or unlock your free trial to see your SaaS and AI risk exposure.

Related reading:

• Your Small Business Guide to Agentic AI Identity & Access Management (2026)

• What Is AI Agent Authentication, and Why Does Your Small Business Need It in 2026?

• Model Context Protocol (MCP) Risk: How to Govern Credentials AI Agents Rely On

• Ebook: The complete guide to AI access governance

Sources

O’Reilly. Fighting tool sprawl: The case for AI tool registries (2026)

Cloud Security Alliance: Token sprawl in the age of AI

Cloud Security Alliance: Vibe Coding security crisis: Credential sprawl and SDLC debt (2026)

Storyboard18: Amazon scales internal AI tools across 700+ teams as adoption accelerates (2026)

Channel Dive: AI creates identity sprawl crisis for channel partners (2026)

Enterprise AI: Faster builds, bigger mess: Amazon’s AI expansion backfires internally (2026)

Tech Radar: Amazon workers are apparently “tokenmaxxing” AI platforms (2026)

The Hacker News. 2026: the year of AI-assisted attacks

Mobile ID World: Japanese teens arrested for using ChatGPT to hack Rakuten Mobile contracts

Verizon: Vulnerability exploitation top breach entry point, 2026 industry-wide DBIR finds