This study investigates the vulnerability of scale-free networks to intentional attack, where a fraction p of the most connected nodes is removed. Scale-free networks have a connectivity distribution P(k) ~ k^(-α). Using percolation theory, the research determines the critical fraction p_c needed to disrupt the network and the size of the largest connected cluster. It is found that even networks with α ≤ 3, known to be resilient to random removal, are sensitive to intentional attack. Near criticality, the average distance between sites in the spanning cluster scales with the cluster's mass M as √M, not log_k M, as expected in random networks. This indicates that intentional attack can disrupt networks before reaching the critical threshold. The Internet is considered a scale-free network with α ≈ 2.5. For α > 3, there is a critical threshold p_c where the network disintegrates upon removal of p > p_c sites. For α ≤ 3, networks are more resilient but can still be disrupted when nearly all sites are removed. Intentional attack, targeting high-connectivity nodes, is highly effective. The critical fraction p_c depends on α and the network size. For α > 2, p_c decreases as α increases, while for α approaching 2, p_c approaches zero, indicating extreme vulnerability. The study also shows that the size of the spanning cluster as a fraction of the remaining sites, P_∞(p), decreases with p. Near criticality, P_∞(p) scales as |p_c - p|, indicating a phase transition. The average distance between sites in the spanning cluster scales as √M near criticality, indicating that communication becomes inefficient even before the cluster is fully disrupted. The study concludes that scale-free networks are highly sensitive to intentional attack, even for α < 3. The results highlight the importance of network design and the potential risks of targeting high-connectivity nodes in scale-free networks.This study investigates the vulnerability of scale-free networks to intentional attack, where a fraction p of the most connected nodes is removed. Scale-free networks have a connectivity distribution P(k) ~ k^(-α). Using percolation theory, the research determines the critical fraction p_c needed to disrupt the network and the size of the largest connected cluster. It is found that even networks with α ≤ 3, known to be resilient to random removal, are sensitive to intentional attack. Near criticality, the average distance between sites in the spanning cluster scales with the cluster's mass M as √M, not log_k M, as expected in random networks. This indicates that intentional attack can disrupt networks before reaching the critical threshold. The Internet is considered a scale-free network with α ≈ 2.5. For α > 3, there is a critical threshold p_c where the network disintegrates upon removal of p > p_c sites. For α ≤ 3, networks are more resilient but can still be disrupted when nearly all sites are removed. Intentional attack, targeting high-connectivity nodes, is highly effective. The critical fraction p_c depends on α and the network size. For α > 2, p_c decreases as α increases, while for α approaching 2, p_c approaches zero, indicating extreme vulnerability. The study also shows that the size of the spanning cluster as a fraction of the remaining sites, P_∞(p), decreases with p. Near criticality, P_∞(p) scales as |p_c - p|, indicating a phase transition. The average distance between sites in the spanning cluster scales as √M near criticality, indicating that communication becomes inefficient even before the cluster is fully disrupted. The study concludes that scale-free networks are highly sensitive to intentional attack, even for α < 3. The results highlight the importance of network design and the potential risks of targeting high-connectivity nodes in scale-free networks.