Solve all your security 'frequently asked questions', and secure your boss's nod of approval during presentations!

Doing cybersecurity in-house at a company means every company has its own skeleton in the closet.

Every year we shout that cybersecurity is important, the budget is allocated, equipment is bought, and people are hired. We work ourselves to the bone all year round, and what's the result?

At meetings, the leadership still asks the same old questions: "How much money have we actually spent on cybersecurity? What has it brought us? Will we increase the budget next year?"

If something goes wrong in a business department, the first thing they think of is probably: "Did cybersecurity restrict something again?"

Sometimes the cybersecurity department is like a combination of a "scapegoat" and a "professional cleaner."

No one remembers you when nothing goes wrong, but once something happens, you are accused by everyone.

Want to prove your worth? It's too difficult!

Saying how much loss we avoided—who would believe that? It's just empty words without proof.

Saying how much capacity we have improved—how do we quantify that? It's just a bunch of incomprehensible technical jargon.

Today, we will talk about those "whys" that keep us tossing and turning, unable to understand, and more importantly, in the face of these "whys", how we can realistically bring the value of cybersecurity work to the table, have more confidence when reporting upwards, and make every penny of investment resonate.

01

Those "whys" that keep us awake at night 1. "What useful things did my Web Application Firewall (WAF) actually block? Can it keep up with the endless stream of new attack techniques?" The logs are like waterfalls, and the real threatening attacks are drowned inside. They talked it up when we bought it, but attack techniques change every day. Can we obtain and transform the latest threat intelligence into effective defense strategies in a timely manner? How often is the rule library of the Web Application Firewall (WAF) updated?

Did we spend a fortune to buy "loneliness"? Or did we buy "outdated peace of mind"?

2. "Vulnerabilities are as numerous as ox hair. Which one should we patch first? Which one is the hacker's most likely next target?"

A scan reveals a massive flood of high and medium-risk vulnerabilities. For those with high CVSS scores, the business department says this system cannot be stopped. Moreover, can hackers really exploit those that are theoretically high-risk? More importantly, among so many vulnerabilities, which ones are Known Exploited Vulnerabilities (KEV), which ones are predicted to be exploited soon based on the latest intelligence (EPSS), and which ones are analyzed by AI to have the highest risk on assets in our specific industry?

Urging IT to patch every day—is it "precision guidance" or "blind shooting"?

3. "What has the newly deployed EDR/XDR actually caught besides making endpoints laggy? Can it intelligently identify those 'cunning' attacks?"

Everyone says behavioral detection is great and can catch unknown threats. What's the result? It's either a bunch of false positives or dead silence with nothing at all. Can it identify those variant attacks generated by AI, or carefully constructed low-and-slow attacks through intelligent analysis?

Is the product no good? Are we not using it right? Or is our "intelligent" defense not "intelligent" enough?

4. "We have done N rounds of security awareness training, but why do people still click on phishing emails? What should we do?"

We have set after set of training materials, and everyone passed the exams. But when a phishing simulation email is sent, the click rate is still so "stable". Is it because employees don't care? Is the training content detached from reality? Or is training alone simply unable to solve the problem?

5. "The leadership asked me, compared with competitor companies, how is our cybersecurity level? Can our investment handle future threats?"

How would I know what's going on with other companies? Even if I did, with different industries and businesses, how do we compare? More importantly, how do we prove that our cybersecurity investment is not just responding to known threats, but is also prepared for potential emerging threats based on intelligence and AI predictions?

Without a benchmark for horizontal comparison, and without forward-looking risk insights, how do we prove the strategic value of the investment?

Do these questions hit close to home? And these "whys" are exactly where we are most likely to get stuck when reporting upwards, and where we need to give clear answers the most.

02

Let cybersecurity effectiveness speak for itself so that upward reporting has substance

Since it's hard to explain, let's not just explain with our mouths. We have to find a way to let the effectiveness of cybersecurity "speak for itself." How?

The core idea is: Don't wait for hackers to attack us. Let's find a way to "attack" ourselves first, by simulating real attacks—ideally combined with the latest threat intelligence and AI intelligent analysis—to turn those "possible," "perhaps," and "theoretical" risks into visible, tangible real-world problems. In this way, when we report upwards, we will have real evidence in hand.

1. Firewalls/IPS/WAF, bring them out for a spin! Practice with the latest playbooks!

• What to do: Don't believe those fancy reports. Find a tool, preferably one that can continuously access the latest threat intelligence and even generate targeted attack simulation scenarios through AI analysis, such as the latest OWASP Top 10 attacks, targeted APT attack fragments, and early penetration behaviors of ransomware, and run them directly against our network boundaries and core applications.

• What to look at: Which attacks were blocked? Which device blocked them? Are they recorded in the logs? Did alerts trigger? Which attacks slipped through as if entering an empty territory? Especially for those attacks simulated based on the latest intelligence, how did our defense system react?

• Reporting Upwards: "Leaders, based on the latest threat intelligence and utilizing AI-assisted generation, we simulated attack scenarios targeted at our company. The results show that our Web Application Firewall has a 90% blocking rate against YY-type attacks, but only 30% against ZZ-type attacks (which intelligence shows have been active recently) that exploit the latest XX vulnerability. Therefore, we recommend adjusting the XX strategy/upgrading the XX module to counter these imminent threats."

2. Vulnerabilities: don't look at the ads, look at the efficacy, and especially look at whether they are hot targets in the eyes of hackers!

• What to do: CVSS scores and EPSS predictions are just references. The key is whether hackers can actually exploit this vulnerability in our environment. A good validation method is to combine it with threat intelligence to tell you if the attack tools related to this vulnerability are already widespread; at the same time, use AI analysis to determine the success probability and potential impact of this vulnerability being exploited under your specific assets and business scenarios.

• What to look at: Which high-risk vulnerabilities are actually "dormant volcanoes" here due to network isolation? Which medium-and-low-risk vulnerabilities have instead become "time bombs" because intelligence shows they have been exploited in the wild, or AI analysis shows they have a high correlation with our key business?

• Reporting Upwards: "Leaders, we discovered 100 high-risk vulnerabilities this month. However, by combining the latest threat intelligence and AI risk assessment, we identified that 5 of them are currently most favored by hackers and directly threaten our core order system. We have prioritized pushing for the remediation of these 5, and the rest are being prioritized based on the comprehensive risk score and business impact provided by AI."

  

3. EDR/XDR, whether it's a horse or a mule, let's test it with variant exam questions!

• What to do: Don't wait until you are actually hacked to think of it. Regularly use some open-source or commercial attack simulation tools to run harmless attack scripts on test endpoints. If these simulations can use AI technology to generate variants of known attacks, or simulate more covert evasion techniques based on machine learning, it will test the intelligence of EDR/XDR even better.

• What to look at: Did EDR/XDR trigger alerts? Is the alert information accurate? Can it pinpoint the attack behavior? Is the response and handling process smooth? Especially in the face of those "non-standard" attacks generated by AI, how is its detection capability?

• Reporting Upwards: "Leaders, we used AI-assisted generation to produce a batch of simulated attack variants and tested the newly deployed EDR. The results show that it successfully detected and blocked 70% of the variant attacks, an increase of XX% in detection rate compared to traditional signature detection. This proves its intelligent analysis capability in dealing with unknown and mutated threats."

4. Cybersecurity awareness? "Fish" and then improve!

• What to do: Continue with training, but more importantly, carry out regularized and diversified phishing simulations. After the simulation, it's not just about criticism and education; we need to analyze: which types of emails are people most likely to fall for? Which department has the highest click rate? Is it a matter of the subject line, or the sender?

• Reporting Upwards: "Leaders, after half a year of continuous phishing simulations and targeted reminders, the phishing email click rate of our XX department has dropped from 30% to 10%, and the proportion of employees proactively reporting suspicious emails has increased by 50%." This is far more valuable than saying "we did XX training sessions."

5. Who do we compare with? Compare with ourselves of yesterday, compare with the latest methods of attackers, and see if we have foresight!

• What to do: Don't always think about comparing with other companies. Establish a "cybersecurity baseline" based on your own business risks and attack simulation results. The establishment and evolution of this baseline should continuously integrate the latest threat intelligence and use AI to predict trends, helping us judge the main risk directions we may face in the future.

• What to look at: Have these indicators improved or worsened? When new attack techniques or threat intelligence emerge, can our existing defense system cover them? How big is the gap? Can our cybersecurity strategy be adjusted in a forward-looking manner based on intelligence and AI warnings?

• Reporting Upwards: "Leaders, compared with half a year ago, we have not only shortened the response time to known attacks by XX%, but more importantly, by continuously introducing threat intelligence and AI analysis, we have identified and reinforced 3 weak links that may be heavily targeted in the future, nipping the trouble in the bud. This is a manifestation of our cybersecurity investment transforming from passive defense to active foresight."

03

BoundaryX Breach and Attack Simulation: AI + Intelligence Dual Engine, Making Validation Smarter and Insights Deeper

BoundaryX Breach and Attack Simulation (BAS) helps everyone do those things of "actively finding trouble" and "bringing them out for a spin" in a more systematic, efficient, secure, and data-backed way. Recently, we released the new version 4.0 of BoundaryX, the core of which lies in the built-in powerful AI engine and threat intelligence engine, making security validation "smarter":

• Want to know if your security products are "running idle"? Want to know even more if they can withstand the latest, or even the next wave of attacks? Our threat intelligence engine will continuously feed the platform with the latest attack techniques and vulnerability exploitation information, while the AI engine can intelligently generate and optimize attack simulation scenarios based on this intelligence and your business environment, ensuring validation always keeps up with the threat frontier.

• Want to know which vulnerability is your biggest headache? Want to make risk assessment more accurate and forward-looking? Our platform will tell you which vulnerabilities are being actively exploited, and the AI engine will comprehensively analyze and intelligently assess the real risk and potential business impact of missed detections in each validation task, helping you precisely locate "compulsory tasks" from a sea of vulnerabilities.

• Want to make reports on cybersecurity investment more convincing? Want to prove that your cybersecurity strategy is not only effective but also visionary? We can provide detailed validation reports, letting the data speak for itself, telling you exactly how much your defense capabilities have realistically improved after every security enhancement. More importantly, validation results based on AI and intelligence can help you articulate how security investments handle known threats and prepare sufficiently for future potential risks. These reports are your most powerful ammunition when reporting upwards.

The core is just one sentence: We help you turn "hypothetical threats" into "verifiable scenarios" and "vague sense of security" into "measurable data." Through the dual empowerment of AI and intelligence, we make your security validation smarter and risk insights deeper, ensuring that every penny you spend can make a sound, allowing you to stand taller in front of the leadership.

Doing cybersecurity in-house is indeed not easy. But we cannot always be trapped in the vicious cycle of "unable to explain, unable to prove." Taking the initiative, speaking with facts and data, and embracing new technologies like AI and intelligence to arm ourselves, might be a path that makes ourselves and the cybersecurity industry more valuable.