DEV Community: Alex

When Should Your Company Hire an Ethical Hacker?

Alex — Thu, 23 Jul 2026 08:58:35 +0000

Shipping a product without testing its security is a little like opening a new office without checking whether the doors lock.

Automated scanners, secure coding practices, endpoint protection, and monitoring all matter. But they do not always show how an attacker could combine several small weaknesses into a meaningful compromise.

That is where an ethical hacker—or, more formally, a penetration tester—can help.

An ethical hacker uses real-world attack techniques to assess systems that an organization owns or is explicitly authorized to test. The objective is defensive: identify exploitable weaknesses, demonstrate their business impact safely, and give the organization a clear remediation plan.

The word authorized is essential. Ethical hacking is not a label someone can apply after accessing a system without permission. A legitimate engagement begins with written approval, an agreed scope, technical limits, and rules of engagement.

Ethical hacking is more than running a scanner

A vulnerability scanner is useful for checking many assets quickly. It can identify known vulnerable software versions, missing patches, exposed services, and common configuration issues.

A penetration test goes further. A skilled tester may:

Validate whether a finding is actually exploitable

Test authentication, authorization, and session management

Review business logic and transaction flows

Combine several low- or medium-severity weaknesses

Evaluate the real impact on data, users, and operations

Provide evidence and remediation guidance

For example, a scanner may detect an access-control issue on one API endpoint. A penetration tester may discover that the issue can be combined with predictable object identifiers to access another customer's records.

Both activities are valuable, but they answer different questions:

Question

Vulnerability scan

Penetration test

Can we check many assets quickly?

Strong fit

Sometimes

Are known vulnerabilities present?

Strong fit

Yes

Can a weakness be exploited?

Limited validation

Strong fit

Does the application contain business-logic flaws?

Limited

Strong fit

What is the realistic business impact?

Limited

Strong fit

Can multiple weaknesses form an attack path?

Rarely

Strong fit

Buying an automated scan while expecting a full penetration test is a common—and potentially expensive—mistake.

When should you hire an ethical hacker?

Not every organization needs a large red-team exercise. However, a focused penetration test is worth considering in several situations.

Before a public launch

Before a website, API, mobile application, or customer portal goes live, a security assessment can uncover problems while they are still easier to fix.

Typical areas include:

Broken authentication or authorization

Insecure session handling

Exposed API operations

Server and cloud misconfiguration

Payment or account-recovery flaws

Business-logic abuse

Testing before launch also reduces the chance of discovering a critical issue after real customer data has entered the system.

After a major architectural change

Significant changes often introduce new trust boundaries and attack paths. Consider another test after:

Migrating workloads to the cloud

Adding partner-facing APIs

Changing the login or identity system

Introducing new payment functionality

Redesigning application architecture

Expanding remote access or the internal network

An update may fix an old vulnerability while creating a new problem through incorrect deployment, excessive permissions, or an unsafe default configuration.

After a security incident

Once an incident has been contained and investigated, a penetration test can help verify whether the original attack path has been closed and whether similar paths remain.

However, penetration testing is not a substitute for incident response or digital forensics. If an attack is still active, prioritize containment, evidence preservation, investigation, and recovery first.

When customers, auditors, or partners require assurance

Customers and business partners increasingly ask for evidence that important systems have been independently assessed. Penetration testing may also support a broader risk-management or compliance program.

A test report should not be treated as a permanent security certificate. It reflects a particular scope, point in time, environment, and methodology.

As part of a risk-based testing cycle

Even without a major release, an organization's attack surface changes continuously. New cloud services appear, accounts accumulate privileges, software dependencies age, and new vulnerabilities are disclosed.

The right testing frequency depends on:

The sensitivity of the data

How often the system changes

Internet exposure

Business criticality

Regulatory or contractual obligations

The organization's threat model

High-change, Internet-facing systems handling sensitive data generally need more frequent assessment than stable, isolated internal tools.

What can be tested?

The scope should follow the business risk rather than a generic service package. Common targets include:

Web applications and websites

Mobile applications

APIs and integrations

Cloud infrastructure

Internet-facing hosts

Internal networks and servers

Wireless networks

Identity and access controls

IoT devices

Social-engineering scenarios, when separately and explicitly authorized

Different targets require different methods. API testing may focus on object-level authorization and transaction logic, while an internal network test may focus on segmentation, exposed services, credential reuse, and privilege escalation.

Authorization and rules of engagement

Before testing begins, both parties should agree in writing on at least:

The domains, IP addresses, applications, APIs, accounts, and environments in scope

The testing start and end times

Permitted and prohibited techniques

Limits on exploitation, privilege escalation, and data access

Emergency contacts and stop conditions

How test data and evidence will be stored, transferred, and destroyed

Responsibility for service disruption or unexpected impact

How critical findings will be escalated

Third-party services should be excluded unless their owners have also provided permission. Cloud platforms, payment gateways, and managed services may have their own testing policies.

Never hire someone to break into another person's email, social-media account, phone, or infrastructure. That is unauthorized access, not ethical hacking. Laws vary by jurisdiction, so organizations should obtain appropriate legal advice when defining an engagement.

Freelancer or penetration-testing company?

A capable freelancer can be a good choice for a small, well-defined assessment—especially when the organization already knows the person's expertise and track record.

For production systems or environments containing sensitive data, the decision involves more than individual technical skill.

Consideration

Freelancer

Testing company

Initial cost

May be lower

Often higher

Breadth of expertise

Depends on one person

May involve multiple specialists

Staff continuity

Limited

Usually easier to manage

Independent review

Depends on the individual

Often part of quality control

Contracts and data handling

Must be checked carefully

Usually more standardized

Remediation support and retesting

Varies

Often a defined process

Certifications such as OSCP or GPEN can be useful signals, but they do not prove that a tester is the right fit for every application, technology stack, or industry.

Ask potential providers for:

Relevant experience with the target technology

Their testing methodology and standards

A sanitized sample report

Data-protection procedures

A nondisclosure agreement

Their critical-finding notification process

A remediation and retesting policy

The name or role of the person reviewing the final report

A commitment not to expand the scope without approval

Warning signs of an untrustworthy provider

Be cautious if a provider:

Promises to compromise any system

Advertises account hacking or surveillance

Does not verify that you own or control the target

Refuses to sign a contract or NDA

Cannot define the scope in writing

Has no plan for service disruption

Delivers only raw output from automated tools

Cannot explain its risk-rating method

Requests unnecessary access

Has no data-retention or destruction policy

Guarantees that your system will become “100% secure”

No professional tester can guarantee permanent security. A penetration test is a time-bound assessment, and new weaknesses can appear after changes to code, infrastructure, configuration, or dependencies.

A practical preparation checklist

Before requesting proposals, prepare:

An inventory of the assets to be tested

The business goal or compliance requirement

A high-level architecture overview

The number and types of user roles

Critical functions and business workflows

The preferred testing environment

Approved testing windows

Third-party systems that must remain out of scope

Technical and emergency contacts

Reporting and retesting expectations

Better preparation leads to more accurate estimates, fewer scope disputes, and results that are easier for engineering teams to act on.

Final takeaway

The value of an ethical-hacking engagement is not simply that someone “managed to hack the system.”

Its real value is helping the organization answer three questions:

Which weaknesses are genuinely exploitable?

What could an attacker achieve?

What should the team fix first?

A useful engagement is authorized, carefully scoped, safely executed, and followed by remediation and retesting. When those conditions are in place, ethical hacking becomes more than a technical exercise—it becomes a practical tool for reducing business risk.

Source and further reading

IPSIP Vietnam: When Should a Business Hire a White-Hat Hacker?

This article is for general informational purposes and does not constitute legal advice.

Is Vibe-Coded web development secure? 7 risks to check before production

Alex — Wed, 22 Jul 2026 04:08:47 +0000

AI coding tools can turn an idea into a working website in hours instead of weeks. The interface looks complete, users can sign in, data is stored, and the product can be deployed almost immediately.

But a website that works is not necessarily a website that is secure.

An application may behave correctly for legitimate users while exposing API keys, allowing one account to access another user’s data, or leaving sensitive endpoints available without authentication.

So, is vibe-coded web development secure?

It can be—but it should never be considered secure by default. The code, APIs, access controls, dependencies, and production configuration still require independent review.

Here are seven security risks to check before deploying an AI-generated website.

1. Exposed API keys and secrets

AI coding assistants often connect applications to databases, payment gateways, email providers, cloud platforms, and external APIs.

To make these integrations work quickly, credentials may be placed directly in the source code or configuration files.

Common examples include:

API keys
Database passwords
JWT signing secrets
OAuth client secrets
Webhook secrets
Cloud access keys
Private keys
Service account credentials

Secrets can also leak through committed .env files, Git history, frontend bundles, source maps, logs, Docker images, CI/CD configurations, error messages, screenshots, or prompts sent to AI tools.

A particularly common mistake is referencing a secret environment variable in frontend code. After the application is built, that value becomes part of the JavaScript downloaded by every browser.

If a secret has been pushed to a public repository, assume it has been compromised. Removing the line later is not enough—the credential should be revoked and rotated.

2. Authentication that only looks secure

A complete login screen does not prove that the backend is protected.

AI-generated applications may include registration, login, logout, password recovery, role selection, and “remember me” functionality while still missing important controls such as:

Login rate limiting
Secure cookie configuration
Reasonable token expiration
Token revocation after password changes
One-time password-reset links
Account verification
Multi-factor authentication
Backend account-status checks

A frequent mistake is protecting only the user interface.

For example, the frontend may redirect unauthenticated users to /login, while the following endpoint still returns customer information without validating a session:

GET /api/customers

Attackers do not need to use the interface. They can call the API directly with scripts, cURL, Postman, or automated security tools.

Authentication must be enforced on the server for every protected request.

3. Broken authorization and cross-user data access

Authentication answers:

Who is the user?

Authorization answers:

What is this user allowed to do?

An application may authenticate users correctly while still exposing data through broken authorization.

Consider this URL:

/orders/1001

If changing 1001 to 1002 reveals another customer’s order, the application is not verifying ownership of the requested resource.

The same issue can affect:

Customer IDs
User IDs
Invoice IDs
Tenant IDs
Project IDs
File IDs
Support tickets
Document download URLs

This is especially dangerous in multi-tenant SaaS applications. A single authorization mistake may allow one company to read or modify another company’s data.

AI-generated code may also fail to understand business rules such as:

A requester cannot approve their own request
Employees may only access records from their department
Managers may view records but not delete them
Trial accounts cannot access paid features
Support agents cannot transfer account ownership
Tenant data must remain completely isolated

These problems usually require manual testing because scanners cannot fully understand business intent.

4. Frontend-only input validation

AI tools frequently add validation to forms: required fields, valid email formats, numeric phone numbers, file extensions, and minimum or maximum values.

However, browser-side validation can be bypassed by sending requests directly to the API.

Attackers may submit:

Negative or extremely large values
Unexpected fields
Modified prices
Administrative roles
Very long strings
HTML or JavaScript
Query fragments
Unusual file paths
Executable files
Oversized payloads

Without server-side validation, the application may become vulnerable to SQL injection, NoSQL injection, cross-site scripting, command injection, path traversal, mass assignment, malicious file uploads, or server-side request forgery.

Treat every value received by the backend as untrusted—even if the frontend already validated it.

5. Unsafe or imaginary dependencies

When asked to implement a new feature, a coding assistant may recommend installing another package.

That package might:

Contain known vulnerabilities
Be abandoned or poorly maintained
Imitate the name of a popular library
Introduce unnecessary transitive dependencies
Use an incompatible license
Run installation scripts
Come from an unknown maintainer
Not actually exist yet

The last case creates a particularly interesting supply-chain risk.

An AI model may generate a plausible package name that does not exist in the registry. An attacker can later register that name and publish malicious code. Developers who follow the AI-generated installation command may then install the attacker’s package.

Malicious dependencies can steal environment variables and tokens, modify source code, compromise CI/CD pipelines, or create persistent access to development systems.

Never install a dependency only because the command succeeds and the original error disappears.

6. Insecure APIs and production configuration

Relatively secure application code can still be deployed in an unsafe environment.

Common configuration problems include:

Databases exposed to the internet
Public storage buckets
Debug mode enabled in production
CORS allowing every origin
Public source maps
Unauthenticated administration dashboards
Forgotten test endpoints
Backups stored in public directories
Stack traces returned to users
Overprivileged service accounts
Demo environments using production data

A prototype may begin as an internal dashboard and later be shared with partners, sent through email, or indexed by a search engine.

Without authentication or network restrictions, an “internal tool” can quietly become a public application.

Security review therefore needs to cover the deployment environment—not just the source code.

7. Overprivileged AI coding agents

The security risk is not limited to generated code. The coding agent itself may become part of the attack surface.

Depending on its configuration, an agent may be able to:

Read an entire repository
Modify or delete files
Execute shell commands
Install packages
Read environment variables
Access databases
Connect to cloud services
Use MCP servers
Deploy applications
Interact directly with production

If the agent processes malicious instructions hidden inside a repository, issue, document, website, email, API response, or package documentation, broad permissions can significantly increase the damage.

A compromised or manipulated agent might expose secrets, install malicious packages, weaken security settings, modify code, or execute dangerous commands.

AI agents should follow the principle of least privilege. Give them only the access required for the current task and keep sensitive production actions behind explicit human review.

Which projects need the most scrutiny?

Not every vibe-coded website has the same risk level.

A static landing page without accounts, stored data, or backend integrations generally carries less risk than a multi-tenant SaaS platform.

Security assessment should be prioritized when the website:

Has user accounts
Stores personal or customer data
Processes payments
Supports multiple roles
Exposes APIs
Uses a multi-tenant architecture
Connects to internal systems
Includes an administration panel
Accepts file uploads
Uses autonomous AI agents
Serves enterprise customers

The greater the business impact of a compromise, the less appropriate it is to rely exclusively on AI-generated security checks.

Final thoughts

Vibe coding does not automatically produce insecure websites.

AI can help teams create prototypes, validate ideas, automate repetitive work, and deliver products faster. The risk appears when code generation moves faster than the team’s ability to review, test, and govern it.

Before an AI-generated website goes into production, the team should be able to answer:

What data does the application process?
Who is allowed to access that data?
Which APIs are publicly available?
Where are secrets stored?
Which dependencies are installed?
What actions can the AI agent perform?
Which failures could affect customers or business operations?
Who is responsible for incident response?

Asking an AI tool to “write secure code” may reduce some mistakes, but it cannot replace code review, API testing, authorization testing, dependency analysis, configuration review, and penetration testing.

For applications with sensitive data or important business logic, the next step should be a verifiable security process—not another prompt asking the AI to review its own work.

The original Vietnamese article is available here:
Are Vibe-Coded websites secure? 7 risks to check

What security issue have you encountered most often in AI-generated applications?

AI-Powered cyber attacks: Why traditional security controls are no longer enough

Alex — Fri, 10 Jul 2026 04:24:19 +0000

Artificial Intelligence has become a standard tool for developers, security teams, and unfortunately, attackers.

While AI boosts productivity for legitimate users, it also enables threat actors to automate tasks that once required significant technical expertise. The result is a new generation of cyberattacks that are faster, more scalable, and increasingly difficult to detect.

How Attackers Are Using AI

AI doesn't magically replace hackers, but it dramatically increases their efficiency.

Some common use cases include:

Generating convincing phishing emails with almost perfect grammar.
Creating fake login pages and social engineering content.
Automating OSINT (Open Source Intelligence) collection.
Writing or modifying malware scripts.
Searching for vulnerable public services.
Assisting in exploit development.
Evading traditional detection mechanisms.

Instead of spending days preparing an attack, threat actors can now automate large parts of the attack chain.

The Biggest Problem Isn't the AI

The biggest problem is that many organizations still defend against modern threats using yesterday's security model.

Typical environments still rely on:

Traditional antivirus
Firewalls
Annual penetration testing
Manual log reviews
Password policies

These controls remain important—but they're no longer sufficient when attackers can continuously adapt using AI.

AI Makes Phishing Much Harder to Detect

Traditional phishing emails often contained obvious spelling mistakes or generic content.

AI-generated phishing campaigns are different.

Attackers can personalize messages using publicly available information from:

LinkedIn
Company websites
GitHub
Social media
Public documents

The email looks authentic because AI understands context.

That's why employee awareness remains one of the most important security controls.

What Security Teams Should Focus On

Rather than asking "How do we stop AI?", security teams should ask:

How quickly can we detect abnormal behavior?
Can we identify lateral movement?
Do we continuously monitor critical assets?
Are vulnerabilities remediated quickly?
Is our incident response process tested regularly?
Are privileged accounts adequately protected?

Security today is less about building a stronger wall and more about reducing attacker dwell time.

Security Is Becoming Continuous

The shift is clear.

Organizations are moving away from periodic security activities toward continuous security operations:

Continuous Vulnerability Management
Continuous Threat Detection
Security Monitoring (SOC)
Threat Hunting
Zero Trust Architecture
Security Awareness Training

AI has accelerated the threat landscape, which means defenders must also automate detection and response wherever possible.

Final Thoughts

AI isn't inherently the problem.

The problem is that attackers are adopting it faster than many organizations are adapting their defenses.

Companies that continue relying solely on traditional perimeter security will likely struggle against increasingly intelligent attack campaigns.

If you're interested in a more comprehensive discussion—including practical business impacts, AI-driven attack scenarios, and defensive recommendations—you can read the original article here:

👉 AI-Powered Cyber Attacks: Challenges and Risks

https://www.ipsip.vn/en/post/ai-powered-cyberattacks-challenges-and-risks

Discussion

How is your team preparing for AI-assisted cyber threats?

AI-powered phishing detection?
SOC automation?
LLM security?
Prompt injection defenses?
AI governance?

I'd love to hear how other engineers and security professionals are approaching this challenge.

AI Ransomware Is No Longer a Theory: What JADEPUFFER Means for Developers and Security Teams

Alex — Thu, 09 Jul 2026 03:30:39 +0000

Most developers use AI to write code, generate documentation, or automate repetitive tasks. But what happens when attackers use the same technology to automate an entire cyberattack?

That's exactly why JADEPUFFER caught my attention.

Unlike traditional ransomware, JADEPUFFER demonstrates how an AI agent can chain together multiple attack stages with minimal human involvement—discovering vulnerabilities, harvesting credentials, moving laterally, and encrypting data.

Whether this becomes mainstream or remains an early proof of concept, it highlights an important shift: AI is becoming an active participant in offensive security.

For developers, this raises several questions:

Are AI applications exposing unnecessary services to the Internet?
Are API keys and secrets stored securely?
How quickly are critical vulnerabilities patched?
Can your monitoring detect behavioral anomalies instead of relying solely on signatures?

Many successful attacks don't require zero-day vulnerabilities. They exploit forgotten services, outdated software, and poor credential management.

As AI lowers the barrier for attackers, secure development practices, continuous vulnerability management, and runtime monitoring become even more important.

I wrote a deeper analysis covering how JADEPUFFER works, why it matters, and what organizations should start doing today.

I'd be interested to hear how other developers and security engineers view this trend. Do you think autonomous AI attacks will become common within the next few years?

🔗 Read the full article: https://www.ipsip.vn/en/post/ai-ransomware-jadepuffer-historic-milestone

Red alert: Job interview phishing scam impersonates 30 big brands to steal Google accounts

Alex — Wed, 08 Jul 2026 07:36:28 +0000

A massive job interview phishing scam is directly targeting marketing professionals by impersonating over 30 global brands (Netflix, Adidas, OpenAI). Hackers utilize sophisticated nested redirects through legitimate platforms (Salesforce, PeopleForce) and a fake login window (Browser-in-the-Browser) to steal Google accounts. Organizations must deploy advanced email security solutions to stop this threat.

Just received an interview invitation from OpenAI, Coca-Cola, or Netflix?

Do not celebrate just yet! Recent reports reveal that over 30 of the world's top corporations are being impersonated in a massive job interview phishing scam aimed directly at your Google account. If you rush to click the scheduling link, total control of your personal data and your company's digital resources could fall into the hands of hackers in an instant.

This article will expose this highly sophisticated phishing tactic and guide you on how to thoroughly protect your systems.

Which brands and targets is this job interview phishing scam impersonating?

This campaign primarily targets marketing professionals by posing as recruiters from over 30 major brands across various sectors, ranging from airlines, food and beverage, to tech and sports.

Aviation and tourism

American Airlines
Booking. com
Delta Air Lines
United Airlines

Food and drinks

Coca-Cola
PepsiCo
Red Bull

Fashion and luxury goods

Adidas
Louis Vuitton
Sephora
Levi's

Recruitment, consulting, and technology

Adobe
Aquent
ManpowerGroup
McKinsey & Company
OpenAI Hotel and marketing
Marriott
Omnicom Group

Entertainment and sports

FIFA
Netflix

According to an analysis by Will Thomas at Team Cymru, this malicious activity has been operating covertly for at least five months. To establish absolute trust, the attackers use the real names and photos of actual human resources specialists (recruiters) working at the impersonated companies.

Fake website impersonating Adidas for scheduling meetings.

Fake website impersonating Adidas for scheduling meetings.
Targeting marketing personnel is a clearly calculated strategy. The Google accounts of these individuals are often linked to the enterprise's advertising management systems, customer databases, and social media networks. Therefore, successfully compromising a Google account creates a perfect stepping stone for hackers to infiltrate deeper into the organization's digital infrastructure.

How do the email phishing tactics and nested redirect techniques work?

Attackers distribute emails containing interview scheduling links, but instead of leading directly to a malicious website, they utilize nested redirects through legitimate platforms to bypass security scanning tools.

Specifically, when candidates click the link in the email, they are routed through the PeopleForce system (a legitimate HR platform), pass through Salesforce Marketing Cloud's domain (ExactTarget), and transit via Wise Agent CRM. Abusing the reputation of these cloud systems allows the phishing links to easily bypass traditional email filters, which typically only evaluate the credibility of the initial link. Only after completing this loop are victims pushed to fake domains that are meticulously designed to look exactly like the original career pages (e.g., adidas-hiring[.]com).

How does the Browser-in-the-Browser (BitB) technique steal Google login credentials?
The Browser-in-the-Browser (BitB) technique creates a fake login window using HTML and CSS directly inside the current webpage, perfectly simulating Google's authentication interface to visually deceive users.

On the fake landing page, users are prompted to click a "Continue with Google" button to confirm their interview schedule. Instead of opening a genuine Google browser window, the site displays a fake pop-up complete with a drawn-on address bar and a security padlock icon. Under the pressure of a job search, most victims drop their guard and proceed to log in. All emails and passwords entered into this virtual interface frame are immediately transmitted straight to the hacker's command server.

The combination of social engineering and the abuse of legitimate cloud infrastructure has turned this campaign into a persistent threat for office workers.

For individuals and internal IT departments, the vital rule is to always verify the recruiter's identity directly through the company's official careers page instead of trusting attached links. To identify BitB techniques, try dragging and dropping the login pop-up window outside the browser's boundaries; if it gets stuck inside the webpage, it is definitively a fake.

Most importantly, enable two-factor authentication (2FA/MFA) for Google accounts to create a shield that blocks unauthorized login attempts even if the password is compromised.

The job interview phishing scam targeting Google accounts exemplifies the dangerous evolution of cybercriminals as they thoroughly exploit trust and legitimate digital platforms. Awareness of redirect tactics or BitB virtual login techniques is essential. However, at the enterprise level, investing in specialized email security solutions is the only key to securing the doorway to the organization's data infrastructure.
Source:
Red alert: Job interview phishing scam impersonates 30 big brands to steal Google accounts

Red alert from Akamai: The explosion of DDoS attacks and API security risks targeting the financial sector

Alex — Fri, 19 Jun 2026 09:01:42 +0000

The latest report from Akamai indicates that the financial sector is now the primary target for web, API, and infrastructure-based DDoS attacks.

Global data shows the median duration of Layer 3 and 4 DDoS attacks in EMEA skyrocketed by 1,033%, while maximum attack sizes increased by 236% compared to the previous year. With 96% of financial leaders reporting at least one API security incident in the past 12 months, organizations must imperatively deploy 24/7 SOC monitoring services and proactive defense solutions to prevent system disruptions.

The rapid expansion of digital channels by financial institutions - such as online banking, real-time payments, and third-party integrations - has inadvertently expanded the attack surface. Cybercriminals and hacktivist groups are exploiting this complexity, escalating standard nuisance attacks into sustained sieges. Facing reports of escalating ransomware and AI-driven automated bots, fortifying DDoS defense solutions for banks is no longer optional but a matter of absolute survival.

Why is financial infrastructure crumbling against DDoS attacks and AI bots?

Reliance on internet-facing devices and third-party applications makes financial systems highly susceptible to overloads. Artificial Intelligence (AI) driven bots help hackers amplify attack scales at unprecedented speeds.

Akamai's research reveals a clear shift in the global cybersecurity landscape. The Asia-Pacific (APAC) region is currently the most targeted for Layer 7 DDoS attacks (accounting for 52%). Meanwhile, the duration of Layer 3 and 4 attacks in the EMEA region experienced a shocking 1,033% increase, jumping from 3 minutes in 2024 to 34 minutes in 2025.

Alarmingly, automation and AI are acting as "steroids" for traditional security risks. Advanced bot activity surged by 147% late in 2025. In one cited case study, 96% of all site traffic was identified as malicious scraping bots. While these sustained attacks may not directly steal data, they possess the capability to paralyze operations, collapse payment systems, and cause massive revenue losses.

API security vulnerabilities and Ransomware: The fatal blind spots of financial organizations

Application Programming Interfaces (APIs) are the "choke points" of the financial industry, accounting for 83% of endpoint incursions. Concurrently, ransomware continues to drain the resources of unprepared organizations.

DDoS attacks in the financial sector are projected to increase in 2026.
APIs are essential tools for connecting apps, services, and customer-facing systems, but they also serve as wide-open doors for hacker infiltration. Data shows the banking sector alone endured 60% of total web attacks and 83% of incursions against API endpoints in 2025.

Furthermore, ransomware prevention and incident response strategies are often neglected. Nearly 80% of financial institutions have faced ransomware attacks in the past two years, yet less than half have adopted advanced security technologies. Regulatory bodies in the UK warn that next-generation AI systems will further intensify the scale, speed, and sophistication of these attacks against financial institutions.

What critical solution groups help maintain system survival?
Generative AI search queries frequently emphasize that countering the threats warned by Akamai requires organizations to immediately apply Zero Trust architectures, continuous information security incident response, and rigorous data monitoring.

Web Application and API Protection (WAAP): Deploying intelligent filters is essential to analyze and intercept abnormal traffic from malicious bots, ensuring the absolute safety of API endpoints.
Multi-layered DDoS attack defense strategy: Financial organizations must equip systems to monitor server load capacity and automatically reroute malicious traffic to maintain service availability.
Deploying a 24/7 Security Operations Center (SOC): Detecting and preventing Ransomware requires round-the-clock continuous monitoring, combining the power of machine learning analysis and top-tier security experts.